{"base_commit": "f794ca5265d38906782506f1ac4e197b4e273fc4", "domain": "density-functional-theory", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-001:v0.1.0@sha256:ba7befeae4625761cb107ea17ff7962f0d7fd45a71eb25cf75369dc93da8f9d3", "environment_image_digest": "sha256:ba7befeae4625761cb107ea17ff7962f0d7fd45a71eb25cf75369dc93da8f9d3", "environment_image_id": "sha256:ba7befeae4625761cb107ea17ff7962f0d7fd45a71eb25cf75369dc93da8f9d3", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-001:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "9ed895761e11ebcd5d3d383429d1b50b2039969eab6be3369298f32077d581dd", "release_id": "001", "repository_url": "https://github.com/aditisingh4812/simplified_tuned_range_separated", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_001", "title": "Repair omega-dependent range-separated PBE workflow in a real PySCF STRSF repository", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-001:v0.1.0@sha256:3cf671ebe637b067246b05330c0c95c82bd0e1445fafaa3de1b6c1c4d1d7cd64", "verifier_image_digest": "sha256:3cf671ebe637b067246b05330c0c95c82bd0e1445fafaa3de1b6c1c4d1d7cd64", "verifier_image_id": "sha256:3cf671ebe637b067246b05330c0c95c82bd0e1445fafaa3de1b6c1c4d1d7cd64", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-001:v0.1.0"}
{"base_commit": "f794ca5265d38906782506f1ac4e197b4e273fc4", "domain": "density-functional-theory", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-002:v0.1.0@sha256:13e8c428f486c685ec92b031e46f3520bac3d4e26b6bdd83fde9826a488b7761", "environment_image_digest": "sha256:13e8c428f486c685ec92b031e46f3520bac3d4e26b6bdd83fde9826a488b7761", "environment_image_id": "sha256:13e8c428f486c685ec92b031e46f3520bac3d4e26b6bdd83fde9826a488b7761", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-002:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "413aae9a4fa7428016b80984ed9c66d8b5e9e3af97d9588571f64fcac7a1dc46", "release_id": "002", "repository_url": "https://github.com/aditisingh4812/simplified_tuned_range_separated", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_002", "title": "Repair an inconsistent reduced validation workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-002:v0.1.0@sha256:a863b98f920e1e9b1aede8bd0460d039628aab19a413cce3dad7417028e1bd1a", "verifier_image_digest": "sha256:a863b98f920e1e9b1aede8bd0460d039628aab19a413cce3dad7417028e1bd1a", "verifier_image_id": "sha256:a863b98f920e1e9b1aede8bd0460d039628aab19a413cce3dad7417028e1bd1a", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-002:v0.1.0"}
{"base_commit": "4d8048b51ee0cc00caa4854844c28b7f892fd908", "domain": "atomistic-machine-learning-data", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-003:v0.1.0@sha256:f161a1e658abd71c5c3abda59b61814a2c5bf140a4826b5598a917d62a258f4e", "environment_image_digest": "sha256:f161a1e658abd71c5c3abda59b61814a2c5bf140a4826b5598a917d62a258f4e", "environment_image_id": "sha256:f161a1e658abd71c5c3abda59b61814a2c5bf140a4826b5598a917d62a258f4e", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-003:v0.1.0", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "public_payload_sha256": "1f00289f07104c48c4894348dc606860079c7e5647e213570bb613d52603927e", "release_id": "003", "repository_url": "https://github.com/deepmodeling/dpdata", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_003", "title": "Repair extxyz stress and virial tensor-label preservation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-003:v0.1.0@sha256:4d2e13b726b99a0c9d302ba913cdaa727c49fdc403b65b68918ec70c1713a790", "verifier_image_digest": "sha256:4d2e13b726b99a0c9d302ba913cdaa727c49fdc403b65b68918ec70c1713a790", "verifier_image_id": "sha256:4d2e13b726b99a0c9d302ba913cdaa727c49fdc403b65b68918ec70c1713a790", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-003:v0.1.0"}
{"base_commit": "0f45761e8ef6ffc093f649b0145788577a62ed33", "domain": "rna-seq-genomic-interval-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-004:v0.1.0@sha256:290695ddb1d2a160142311b604ccb61ff5d51d9500b6d218c56b43cbb94d9620", "environment_image_digest": "sha256:290695ddb1d2a160142311b604ccb61ff5d51d9500b6d218c56b43cbb94d9620", "environment_image_id": "sha256:290695ddb1d2a160142311b604ccb61ff5d51d9500b6d218c56b43cbb94d9620", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-004:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "c++", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "8cc8d65610e3d79b5906805b086ce8163a7f03a586bfcbc62badbe9c62d8c555", "release_id": "004", "repository_url": "https://github.com/arq5x/bedtools2", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_004", "title": "Repair split-read exon-overlap filtering", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-004:v0.1.0@sha256:2553def59dc88f1886ad281da1d561600560a6f8391f177d33bb9f4975e7cc4f", "verifier_image_digest": "sha256:2553def59dc88f1886ad281da1d561600560a6f8391f177d33bb9f4975e7cc4f", "verifier_image_id": "sha256:2553def59dc88f1886ad281da1d561600560a6f8391f177d33bb9f4975e7cc4f", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-004:v0.1.0"}
{"base_commit": "", "domain": "magnetic-resonance-spectroscopy-processing", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-matlab-octave-task-005:v0.1.0@sha256:a2c49556f75e3dc3fd7f186e6309b2af8def8b724a950abe28fec9c317043440", "environment_image_digest": "sha256:a2c49556f75e3dc3fd7f186e6309b2af8def8b724a950abe28fec9c317043440", "environment_image_id": "sha256:a2c49556f75e3dc3fd7f186e6309b2af8def8b724a950abe28fec9c317043440", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-matlab-octave-task-005:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "matlab-octave", "license_gate": "none", "license_source": "LICENSE.md", "public_payload_sha256": "dafbff8689114068d979e814bece33e26c954a846a4ce816e3ee4614552ae813", "release_id": "005", "repository_url": "https://github.com/schorschinho/osprey", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_005", "title": "Repair edited MRS subspectrum polarity handling", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-matlab-octave-task-005:v0.1.0@sha256:a7504e832bbcdd27a696ef1a476ae48afae9b470fcb38037c5eb24fd30ccf3b0", "verifier_image_digest": "sha256:a7504e832bbcdd27a696ef1a476ae48afae9b470fcb38037c5eb24fd30ccf3b0", "verifier_image_id": "sha256:a7504e832bbcdd27a696ef1a476ae48afae9b470fcb38037c5eb24fd30ccf3b0", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-matlab-octave-task-005:v0.1.0"}
{"base_commit": "ac6b252a3a6df2498757d76190b2b164cc591453", "domain": "genomics-interval-statistics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-006:v0.1.0@sha256:f740af3206582652b34972f662852a98c370ab94b5e4c1fccb88d065f8abae04", "environment_image_digest": "sha256:f740af3206582652b34972f662852a98c370ab94b5e4c1fccb88d065f8abae04", "environment_image_id": "sha256:f740af3206582652b34972f662852a98c370ab94b5e4c1fccb88d065f8abae04", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-006:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "c++", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "13d72d9ddbb69f144a85b474cae6106efe5bb7198ab09e144771589a4639ebc3", "release_id": "006", "repository_url": "https://github.com/arq5x/bedtools2", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_006", "title": "Repair inconsistent genomic interval enrichment counts", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-006:v0.1.0@sha256:21e0cc23312edf271bb76b5cb35e61125952ff0056813c8e15c52713b6a2e5f9", "verifier_image_digest": "sha256:21e0cc23312edf271bb76b5cb35e61125952ff0056813c8e15c52713b6a2e5f9", "verifier_image_id": "sha256:21e0cc23312edf271bb76b5cb35e61125952ff0056813c8e15c52713b6a2e5f9", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-006:v0.1.0"}
{"base_commit": "2254ab2ae6194b41487c933039c5f2ea204e5107", "domain": "magnetic-resonance-spectroscopy", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-007:v0.1.0@sha256:3d7361fdd902b7603b13befdaee0d7a2bcfb2d1f3f970633c981bd5b975103ec", "environment_image_digest": "sha256:3d7361fdd902b7603b13befdaee0d7a2bcfb2d1f3f970633c981bd5b975103ec", "environment_image_id": "sha256:3d7361fdd902b7603b13befdaee0d7a2bcfb2d1f3f970633c981bd5b975103ec", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-007:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "212b3be3c819f1587ea5e3bed18c94872ce7325e527a521f51ab37680bbfb004", "release_id": "007", "repository_url": "https://github.com/openmrslab/suspect", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_007", "title": "Repair unstable spectral registration for drifted MRS transients", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-007:v0.1.0@sha256:ba9b6eeba1b6ac397d7878bff2d920b1137caf4fda6909422fa9001aab26b24b", "verifier_image_digest": "sha256:ba9b6eeba1b6ac397d7878bff2d920b1137caf4fda6909422fa9001aab26b24b", "verifier_image_id": "sha256:ba9b6eeba1b6ac397d7878bff2d920b1137caf4fda6909422fa9001aab26b24b", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-007:v0.1.0"}
{"base_commit": "ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "domain": "plasma-stability", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-008:v0.1.0@sha256:e65d078c640c84fcd915c520a99d477b3c650ec137056a552ea8aa505d0a19ec", "environment_image_digest": "sha256:e65d078c640c84fcd915c520a99d477b3c650ec137056a552ea8aa505d0a19ec", "environment_image_id": "sha256:e65d078c640c84fcd915c520a99d477b3c650ec137056a552ea8aa505d0a19ec", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-008:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "public_payload_sha256": "5863511b16e2bc29b11d73a3a9672f7d7ef1ff621d544f44a273642013eaad48", "release_id": "008", "repository_url": "https://github.com/PlasmaControl/DESC", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_008", "title": "Establish first vacuum-plus-wall external-region capability in the TERPSICHORE-native path", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-008:v0.1.0@sha256:5f02708ac41337aa21e611a45fc0b398613378833718f2900a18ae753808974a", "verifier_image_digest": "sha256:5f02708ac41337aa21e611a45fc0b398613378833718f2900a18ae753808974a", "verifier_image_id": "sha256:5f02708ac41337aa21e611a45fc0b398613378833718f2900a18ae753808974a", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-008:v0.1.0"}
{"base_commit": "ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "domain": "plasma-stability", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-009:v0.1.0@sha256:a40f148e84915c6a8b0cf89b8cf6ce27d7aedb4451c4bcaee715a55b295831e4", "environment_image_digest": "sha256:a40f148e84915c6a8b0cf89b8cf6ce27d7aedb4451c4bcaee715a55b295831e4", "environment_image_id": "sha256:a40f148e84915c6a8b0cf89b8cf6ce27d7aedb4451c4bcaee715a55b295831e4", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-009:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "public_payload_sha256": "0cfbfaa362cd8e9fa53fd20bd7691c32f0daed12632b711d29e6fc2d45316493", "release_id": "009", "repository_url": "https://github.com/PlasmaControl/DESC", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_009", "title": "Enable projection-wall external-region support in the TERPSICHORE-native path", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-009:v0.1.0@sha256:73746f77074cfc0a1b7abaebf7f95d877a883a454eb8e4e48ef5db52c5ccceac", "verifier_image_digest": "sha256:73746f77074cfc0a1b7abaebf7f95d877a883a454eb8e4e48ef5db52c5ccceac", "verifier_image_id": "sha256:73746f77074cfc0a1b7abaebf7f95d877a883a454eb8e4e48ef5db52c5ccceac", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-009:v0.1.0"}
{"base_commit": "ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "domain": "plasma-stability", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-010:v0.1.0@sha256:647be22b8cc7a897a02a21d624e72a02f3ee49ff44f6524e85d6e244ecb677a7", "environment_image_digest": "sha256:647be22b8cc7a897a02a21d624e72a02f3ee49ff44f6524e85d6e244ecb677a7", "environment_image_id": "sha256:647be22b8cc7a897a02a21d624e72a02f3ee49ff44f6524e85d6e244ecb677a7", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-010:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "public_payload_sha256": "dffb8a232fcdf0541d6536a2ddfc22ec92e5e68aa704ee5e49b19f75cdfd21b3", "release_id": "010", "repository_url": "https://github.com/PlasmaControl/DESC", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_010", "title": "Complete alternate perturbation-representation support", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-010:v0.1.0@sha256:fe5b09f4a5b92039fc793cd50a3feb28c9828eed93a42e4392fb2ea0d0402d11", "verifier_image_digest": "sha256:fe5b09f4a5b92039fc793cd50a3feb28c9828eed93a42e4392fb2ea0d0402d11", "verifier_image_id": "sha256:fe5b09f4a5b92039fc793cd50a3feb28c9828eed93a42e4392fb2ea0d0402d11", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-010:v0.1.0"}
{"base_commit": "ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "domain": "plasma-stability", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-011:v0.1.0@sha256:9ad40bda1a487a22ba30afd79d7c99cc16533444404a653f74c21c189855acbc", "environment_image_digest": "sha256:9ad40bda1a487a22ba30afd79d7c99cc16533444404a653f74c21c189855acbc", "environment_image_id": "sha256:9ad40bda1a487a22ba30afd79d7c99cc16533444404a653f74c21c189855acbc", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-011:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "public_payload_sha256": "28c1ef74121cffdb5d98bd3c3bceb889a974a02f638de61d916b784f1c27f153", "release_id": "011", "repository_url": "https://github.com/PlasmaControl/DESC", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_011", "title": "Complete the Missing Response Capability", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-011:v0.1.0@sha256:a2cce1bf22739b0728b7de005fb8bf8473fd95cc362409fc529a918dd4ca87b7", "verifier_image_digest": "sha256:a2cce1bf22739b0728b7de005fb8bf8473fd95cc362409fc529a918dd4ca87b7", "verifier_image_id": "sha256:a2cce1bf22739b0728b7de005fb8bf8473fd95cc362409fc529a918dd4ca87b7", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-011:v0.1.0"}
{"base_commit": "ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "domain": "plasma-stability", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-012:v0.1.0@sha256:4b4284b2dddfead4001e9be44b2dc8807b7b30043dff03541cbfe925bf44b066", "environment_image_digest": "sha256:4b4284b2dddfead4001e9be44b2dc8807b7b30043dff03541cbfe925bf44b066", "environment_image_id": "sha256:4b4284b2dddfead4001e9be44b2dc8807b7b30043dff03541cbfe925bf44b066", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-012:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "public_payload_sha256": "1b3d9c866f207e617fec2d02f7f907fb8825a73dddaf58c8e3ea8428efd36e36", "release_id": "012", "repository_url": "https://github.com/PlasmaControl/DESC", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_012", "title": "Complete 3-D Cross-n FOURIN Spectral Coupling", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-012:v0.1.0@sha256:3ccc8ecdaed2fce6d60b926a927315995930a3f75a1713470564b11f2622e47c", "verifier_image_digest": "sha256:3ccc8ecdaed2fce6d60b926a927315995930a3f75a1713470564b11f2622e47c", "verifier_image_id": "sha256:3ccc8ecdaed2fce6d60b926a927315995930a3f75a1713470564b11f2622e47c", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-012:v0.1.0"}
{"base_commit": "ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "domain": "plasma-stability", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-013:v0.1.0@sha256:440fac5af67d594f3353b77e800fd23a0b0b57c6ce8b491cfa96fa70f8386ae6", "environment_image_digest": "sha256:440fac5af67d594f3353b77e800fd23a0b0b57c6ce8b491cfa96fa70f8386ae6", "environment_image_id": "sha256:440fac5af67d594f3353b77e800fd23a0b0b57c6ce8b491cfa96fa70f8386ae6", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-013:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "public_payload_sha256": "26223383f9ae3d913f440b76d92579dbf8a8db816c578b4b3f9d1ceacac2f0d5", "release_id": "013", "repository_url": "https://github.com/PlasmaControl/DESC", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_013", "title": "Establish boundary-regime operator and energy closure in the TERPSICHORE-native path", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-013:v0.1.0@sha256:f68b8c823724cca42f43145922859e183a018c5ea9c4205fe5b61e3ecebac878", "verifier_image_digest": "sha256:f68b8c823724cca42f43145922859e183a018c5ea9c4205fe5b61e3ecebac878", "verifier_image_id": "sha256:f68b8c823724cca42f43145922859e183a018c5ea9c4205fe5b61e3ecebac878", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-013:v0.1.0"}
{"base_commit": "ab1c5a33031a2e64581f5e663ef8e2f6203a5220", "domain": "plasma-stability", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-014:v0.1.0@sha256:d43ca8fee4244a69302cb5c69bbefa88e6ded15761589ed73c56f2e6077ffb10", "environment_image_digest": "sha256:d43ca8fee4244a69302cb5c69bbefa88e6ded15761589ed73c56f2e6077ffb10", "environment_image_id": "sha256:d43ca8fee4244a69302cb5c69bbefa88e6ded15761589ed73c56f2e6077ffb10", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-014:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "96a3a4ff010c69e1334bd8f8ca21d9461508c60e7bdcc76d6982e7519a3dd5f7", "release_id": "014", "repository_url": "https://github.com/PlasmaControl/DESC", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_014", "title": "Complete the native multi-equilibrium TERPSICHORE workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-014:v0.1.0@sha256:9d4ec1597ff0ea20e8355f790a4d8fcb0198dec12a7ccfefe6a18cdd205b7362", "verifier_image_digest": "sha256:9d4ec1597ff0ea20e8355f790a4d8fcb0198dec12a7ccfefe6a18cdd205b7362", "verifier_image_id": "sha256:9d4ec1597ff0ea20e8355f790a4d8fcb0198dec12a7ccfefe6a18cdd205b7362", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-014:v0.1.0"}
{"base_commit": "", "domain": "magnetic-resonance-spin-dynamics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-matlab-octave-task-015:v0.1.1@sha256:dfbaf9889f662d1ee80e64af404f249a409006fd7f31b41c4c36109e4dcd26b8", "environment_image_digest": "sha256:dfbaf9889f662d1ee80e64af404f249a409006fd7f31b41c4c36109e4dcd26b8", "environment_image_id": "sha256:dfbaf9889f662d1ee80e64af404f249a409006fd7f31b41c4c36109e4dcd26b8", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-matlab-octave-task-015:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "matlab-octave", "license_gate": "none", "license_source": "LICENSE.md", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "af27bc600100b47a8f5e5bf4102267581618fe4720fbad521134ab3e0923f9d2", "release_id": "015", "repository_url": "https://github.com/IlyaKuprov/Spinach", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_015", "title": "Restore thermal-equilibrium invariants in a Liouville-space relaxation workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-matlab-octave-task-015:v0.1.1@sha256:1715bcb15924adee88f48c6c62ef62753f5a033f55f198dbbb9fcf83018661e8", "verifier_image_digest": "sha256:1715bcb15924adee88f48c6c62ef62753f5a033f55f198dbbb9fcf83018661e8", "verifier_image_id": "sha256:1715bcb15924adee88f48c6c62ef62753f5a033f55f198dbbb9fcf83018661e8", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-matlab-octave-task-015:v0.1.1"}
{"base_commit": "a341a2f0ede26735f744d6d5e3b0f7ac1861cfe9", "domain": "chromatin-accessibility peak calling", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-cython-task-016:v0.1.1@sha256:50ba8004fecd5c4671e832e7bbd7535acf376c00961bf815d90c26f269af3681", "environment_image_digest": "sha256:50ba8004fecd5c4671e832e7bbd7535acf376c00961bf815d90c26f269af3681", "environment_image_id": "sha256:50ba8004fecd5c4671e832e7bbd7535acf376c00961bf815d90c26f269af3681", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-cython-task-016:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python-cython", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "f5081627aa86c9f9d3d969a2ee3aafc57da27d078b1da0987c6fb2e619a5eee0", "release_id": "016", "repository_url": "https://github.com/macs3-project/MACS", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_016", "title": "Repair HMMRATAC peak refinement under sparse signal resolution", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cython-task-016:v0.1.1@sha256:0f5faca298805d01f881ef0b1dbf658995fc725b850452eb5832a1e627272248", "verifier_image_digest": "sha256:0f5faca298805d01f881ef0b1dbf658995fc725b850452eb5832a1e627272248", "verifier_image_id": "sha256:0f5faca298805d01f881ef0b1dbf658995fc725b850452eb5832a1e627272248", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cython-task-016:v0.1.1"}
{"base_commit": "", "domain": "gamma-ray-astronomy-dark-matter", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-017:v0.1.1@sha256:3e36e02ed06d5441ad5e03dbe176dfbcebdb832fe4c186847dc292e3a0a46c7c", "environment_image_digest": "sha256:3e36e02ed06d5441ad5e03dbe176dfbcebdb832fe4c186847dc292e3a0a46c7c", "environment_image_id": "sha256:3e36e02ed06d5441ad5e03dbe176dfbcebdb832fe4c186847dc292e3a0a46c7c", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-017:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.rst", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "476c49a1d6b135cff30022badc617bc976d384dc4fa3470c8255334cfcfc1175", "release_id": "017", "repository_url": "https://github.com/gammapy/gammapy", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_017", "title": "Repair dark-matter line-of-sight maps in Gammapy", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-017:v0.1.1@sha256:400c6aa09d0bf39b2af577ba203f9c194bef16d82420b9d79cabcde5a65a6bdf", "verifier_image_digest": "sha256:400c6aa09d0bf39b2af577ba203f9c194bef16d82420b9d79cabcde5a65a6bdf", "verifier_image_id": "sha256:400c6aa09d0bf39b2af577ba203f9c194bef16d82420b9d79cabcde5a65a6bdf", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-017:v0.1.1"}
{"base_commit": "f01cb680e239192484ab672b9e34531b1403eb3d", "domain": "epigenomics-atac-seq-hmm", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-cython-task-018:v0.1.1@sha256:89e99d411185696887e7f538559b5b6b7e96ef80826e567686b38a7c236ba0e6", "environment_image_digest": "sha256:89e99d411185696887e7f538559b5b6b7e96ef80826e567686b38a7c236ba0e6", "environment_image_id": "sha256:89e99d411185696887e7f538559b5b6b7e96ef80826e567686b38a7c236ba0e6", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-cython-task-018:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python-cython", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "ad3688322c62612c1fec8dc19b8a57624ede929b541d54972e719d4f1f253ab8", "release_id": "018", "repository_url": "https://github.com/macs3-project/MACS", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_018", "title": "Restore blacklist semantics in an HMMRATAC chromatin-accessibility workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cython-task-018:v0.1.1@sha256:8b1dd5120cf838ae85b5b2824d2d9fdf419b830b49127d10e3c0d34ef38ead8e", "verifier_image_digest": "sha256:8b1dd5120cf838ae85b5b2824d2d9fdf419b830b49127d10e3c0d34ef38ead8e", "verifier_image_id": "sha256:8b1dd5120cf838ae85b5b2824d2d9fdf419b830b49127d10e3c0d34ef38ead8e", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cython-task-018:v0.1.1"}
{"base_commit": "cb5f54111d2affd89ad732c20c14dab6138026f0", "domain": "single-cell-chromatin-accessibility", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-019:v0.1.1@sha256:2640cbaa3fbd5ede86dd353b7f48173230d80448581bbacc6d434b9a13f9966c", "environment_image_digest": "sha256:2640cbaa3fbd5ede86dd353b7f48173230d80448581bbacc6d434b9a13f9966c", "environment_image_id": "sha256:2640cbaa3fbd5ede86dd353b7f48173230d80448581bbacc6d434b9a13f9966c", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-019:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "noncommercial", "license_source": "source/LICENSE.txt", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "c4b61cbc1c1a90b7f7263eb3c0536a2595d0d3c66d7ee9b83633b576ad02123b", "release_id": "019", "repository_url": "https://github.com/aertslab/pycisTopic", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Academic-NonCommercial", "status": "dockerhub-published", "task_path": "tasks/task_019", "title": "Complete robust topic-to-cistrome binarization for independent probability matrices", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-019:v0.1.1@sha256:ffba9cf85dd9585323f72ac3e160da993c4f9ebb66846aa95071a62346e62330", "verifier_image_digest": "sha256:ffba9cf85dd9585323f72ac3e160da993c4f9ebb66846aa95071a62346e62330", "verifier_image_id": "sha256:ffba9cf85dd9585323f72ac3e160da993c4f9ebb66846aa95071a62346e62330", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-019:v0.1.1"}
{"base_commit": "44f44acb2b9a56f55609ec7f0594d9b6fa01cb92", "domain": "atomistic-machine-learning-and-molecular-simulation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-020:v0.1.1@sha256:da151294981c7487cd2b48c3b2f95eee3a66afca3ff00e2ea1e8bc4e24dc8443", "environment_image_digest": "sha256:da151294981c7487cd2b48c3b2f95eee3a66afca3ff00e2ea1e8bc4e24dc8443", "environment_image_id": "sha256:da151294981c7487cd2b48c3b2f95eee3a66afca3ff00e2ea1e8bc4e24dc8443", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-020:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "source/LICENSE", "material_license": "LGPL-3.0-or-later", "material_license_source": "environment/repo/LICENSE", "material_restricted": true, "material_restricted_reason": "The task source is an LGPL-3.0-or-later DeePMD-kit excerpt.", "materials_gate": true, "public_payload_sha256": "5adc95172533092b7337414f234e4502f3c394ea5dc46e318d8066afb4824212", "release_id": "020", "repository_url": "https://github.com/deepmodeling/deepmd-kit", "restricted_license": true, "restricted_reason": "The task source is an LGPL-3.0-or-later DeePMD-kit excerpt; explicit restricted-license opt-in is required.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-or-later", "status": "dockerhub-published", "task_path": "tasks/task_020", "title": "Complete an edge-graph geometry and force/virial capability for atomistic models", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-020:v0.1.1@sha256:373d19decc97090d881cd8c39d3e9b8eeb9481ec4f7d2dfdda10b29ec11b92f6", "verifier_image_digest": "sha256:373d19decc97090d881cd8c39d3e9b8eeb9481ec4f7d2dfdda10b29ec11b92f6", "verifier_image_id": "sha256:373d19decc97090d881cd8c39d3e9b8eeb9481ec4f7d2dfdda10b29ec11b92f6", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-020:v0.1.1"}
{"base_commit": "9d90fd83c1eec85b7e204bb87f281df0b592623a", "domain": "atomistic thermodynamic integration and free-energy calculation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-021:v0.1.1@sha256:67e1047313c9010d69249bed758dfad28ef6108ac3627b3ae39149fcbb90a00e", "environment_image_digest": "sha256:67e1047313c9010d69249bed758dfad28ef6108ac3627b3ae39149fcbb90a00e", "environment_image_id": "sha256:67e1047313c9010d69249bed758dfad28ef6108ac3627b3ae39149fcbb90a00e", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-021:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "dd6fb60643f7b22fd56015f0d3b55317f55d72fbd7593b4bbffddfebefd29774", "release_id": "021", "repository_url": "https://github.com/deepmodeling/dpti", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_021", "title": "Complete a missing atomic-liquid thermodynamic-integration capability", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-021:v0.1.1@sha256:4556f2a24cf62743731721b1c2e36f82a08ca5c173f639e47b305e93bcd2013d", "verifier_image_digest": "sha256:4556f2a24cf62743731721b1c2e36f82a08ca5c173f639e47b305e93bcd2013d", "verifier_image_id": "sha256:4556f2a24cf62743731721b1c2e36f82a08ca5c173f639e47b305e93bcd2013d", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-021:v0.1.1"}
{"base_commit": "fefa4d30c262384ebda0f1123a1691abf466a9f0", "domain": "neuroimaging", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-022:v0.1.1@sha256:0c0ed46caaa7b0d52a862dad6461ebdc165396fe7f96e8e50df3e4fed8155cf2", "environment_image_digest": "sha256:0c0ed46caaa7b0d52a862dad6461ebdc165396fe7f96e8e50df3e4fed8155cf2", "environment_image_id": "sha256:0c0ed46caaa7b0d52a862dad6461ebdc165396fe7f96e8e50df3e4fed8155cf2", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-022:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "99582a2c2af2ba02e144bae7f74fc0d2921c2b6f81e05bb9be8dcc8de6f6fe74", "release_id": "022", "repository_url": "https://github.com/nilearn/nilearn", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_022", "title": "Repair an inconsistent volume-to-surface projection", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-022:v0.1.1@sha256:ae3adfc761d0744164c6e5e45f686cd766b5ceb1ac17c8c590ce074e0dee938e", "verifier_image_digest": "sha256:ae3adfc761d0744164c6e5e45f686cd766b5ceb1ac17c8c590ce074e0dee938e", "verifier_image_id": "sha256:ae3adfc761d0744164c6e5e45f686cd766b5ceb1ac17c8c590ce074e0dee938e", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-022:v0.1.1"}
{"base_commit": "2acd594449c02c2a354b07291031d89b50b52186", "domain": "molecular-dynamics-periodic-boundary-analysis", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-023:v0.1.1@sha256:26adc2c4f41e400af9bd961ffbfd52711abd2f7a1856deac6eb462d4c6ebf8f9", "environment_image_digest": "sha256:26adc2c4f41e400af9bd961ffbfd52711abd2f7a1856deac6eb462d4c6ebf8f9", "environment_image_id": "sha256:26adc2c4f41e400af9bd961ffbfd52711abd2f7a1856deac6eb462d4c6ebf8f9", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-023:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "153dcbad858d54261690a0f653963b8ef0fcbdb44087021be51c37bc07fc0f30", "release_id": "023", "repository_url": "https://github.com/MDAnalysis/mdanalysis", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "AGPL-family", "status": "dockerhub-published", "task_path": "tasks/task_023", "title": "Restore continuous NPT periodic-boundary unwrapping", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-023:v0.1.1@sha256:20999504b153a946750db97cc28b7458975f6399b7e146350955a1532ad140f4", "verifier_image_digest": "sha256:20999504b153a946750db97cc28b7458975f6399b7e146350955a1532ad140f4", "verifier_image_id": "sha256:20999504b153a946750db97cc28b7458975f6399b7e146350955a1532ad140f4", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-023:v0.1.1"}
{"base_commit": "9ee5d84b5048aea0690bba2629ece684656ad186", "domain": "probabilistic-scientific-computing", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-024:v0.1.1@sha256:6432ca66d7b714d23f5ce315cc1b3ce39dcf7937046d46be4bb470d059c92dcd", "environment_image_digest": "sha256:6432ca66d7b714d23f5ce315cc1b3ce39dcf7937046d46be4bb470d059c92dcd", "environment_image_id": "sha256:6432ca66d7b714d23f5ce315cc1b3ce39dcf7937046d46be4bb470d059c92dcd", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-024:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "ae7eec5199ff7cd1363660c5a2d49e369dbb293f720a4d40b77d6b4628945b82", "release_id": "024", "repository_url": "https://github.com/pymc-devs/pymc", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_024", "title": "Restore coherent inference in a centered factorial-effects model", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-024:v0.1.1@sha256:e641ce128a4db3c75da315e0b85872c2f65a064badbb5e05a972fc4a71b2c30b", "verifier_image_digest": "sha256:e641ce128a4db3c75da315e0b85872c2f65a064badbb5e05a972fc4a71b2c30b", "verifier_image_id": "sha256:e641ce128a4db3c75da315e0b85872c2f65a064badbb5e05a972fc4a71b2c30b", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-024:v0.1.1"}
{"base_commit": "24e89ec3ac278cc642ce06cbbe30321155435e0b", "domain": "edited-magnetic-resonance-spectroscopy-workflow", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-matlab-octave-task-025:v0.1.1@sha256:eebf7a8137f4a36b5d7f27d49bf52596cf342700ca016f003c723f1affab8626", "environment_image_digest": "sha256:eebf7a8137f4a36b5d7f27d49bf52596cf342700ca016f003c723f1affab8626", "environment_image_id": "sha256:eebf7a8137f4a36b5d7f27d49bf52596cf342700ca016f003c723f1affab8626", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-matlab-octave-task-025:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "matlab-octave", "license_gate": "none", "license_source": "LICENSE.md", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "f18821a41645c7f3e74d9406a0194df1526c47fa3f2538177fe027e5685252e3", "release_id": "025", "repository_url": "https://github.com/schorschinho/osprey", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_025", "title": "Repair inconsistent cross-protocol Osprey validation reports", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-matlab-octave-task-025:v0.1.1@sha256:8da94067fe1009753dc73eaf8410b8fe743212c8c1929cc43cb450d3292aac01", "verifier_image_digest": "sha256:8da94067fe1009753dc73eaf8410b8fe743212c8c1929cc43cb450d3292aac01", "verifier_image_id": "sha256:8da94067fe1009753dc73eaf8410b8fe743212c8c1929cc43cb450d3292aac01", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-matlab-octave-task-025:v0.1.1"}
{"base_commit": "34d14b293c9e75dfff5422c0461d48731916d773", "domain": "atmospheric-science-isentropic-interpolation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-026:v0.1.1@sha256:425b952ba92036d8fe6b7a240e0ee7a57ceafc456e68e8297d8d814e06988593", "environment_image_digest": "sha256:425b952ba92036d8fe6b7a240e0ee7a57ceafc456e68e8297d8d814e06988593", "environment_image_id": "sha256:425b952ba92036d8fe6b7a240e0ee7a57ceafc456e68e8297d8d814e06988593", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-026:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "noncommercial", "license_source": "LICENSE", "material_license": "Academic-NonCommercial", "material_license_source": "https://www2.mmm.ucar.edu/wrf/users/docs/technote/v4_technote.pdf", "material_restricted": true, "public_payload_sha256": "f09599c091fa7bce58541cc2b81f32cddfb22bd9d16ca45f87fea1877e871aa3", "release_id": "026", "repository_url": "https://github.com/Unidata/MetPy", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_026", "title": "Restore isentropic interpolation for terrain-following model data", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-026:v0.1.1@sha256:46fadf320df6b6adca39a81c2e83a3f16f8fa486a2adfefdc56a0518edb5db45", "verifier_image_digest": "sha256:46fadf320df6b6adca39a81c2e83a3f16f8fa486a2adfefdc56a0518edb5db45", "verifier_image_id": "sha256:46fadf320df6b6adca39a81c2e83a3f16f8fa486a2adfefdc56a0518edb5db45", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-026:v0.1.1"}
{"base_commit": "9e59a111d201c1c3aee6db079fe1ea2c6a2d8ba8", "domain": "ai4science-nmr-structure-elucidation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-027:v0.1.1@sha256:a0b2b795f21ebf2107c72a04657c3f5dedf1ef816974bedf0e765e8f3d1feafe", "environment_image_digest": "sha256:a0b2b795f21ebf2107c72a04657c3f5dedf1ef816974bedf0e765e8f3d1feafe", "environment_image_id": "sha256:a0b2b795f21ebf2107c72a04657c3f5dedf1ef816974bedf0e765e8f3d1feafe", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-027:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "79aadb8a7614f24d2868a1e8d9bf303ea506294b937f5a76ae98a02cbe4eeb68", "release_id": "027", "repository_url": "https://github.com/little1d/NMRTrans", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_027", "title": "Restore consistent NMR peak-set encoding under batch padding", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-027:v0.1.1@sha256:7553e8b9d60ddba9b86ee74d4f200929dfaed195b79a7e29efa3713f93e5a656", "verifier_image_digest": "sha256:7553e8b9d60ddba9b86ee74d4f200929dfaed195b79a7e29efa3713f93e5a656", "verifier_image_id": "sha256:7553e8b9d60ddba9b86ee74d4f200929dfaed195b79a7e29efa3713f93e5a656", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-027:v0.1.1"}
{"base_commit": "cbedc58e2127d912895defa95c65a623fa2f67d6", "domain": "single-cell-perturbation-response-modeling", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-028:v0.1.1@sha256:c9ed2829a11ec5fc42b54d30bbcd8e2b51f82061a7c0476564d073ed66f3d915", "environment_image_digest": "sha256:c9ed2829a11ec5fc42b54d30bbcd8e2b51f82061a7c0476564d073ed66f3d915", "environment_image_id": "sha256:c9ed2829a11ec5fc42b54d30bbcd8e2b51f82061a7c0476564d073ed66f3d915", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-028:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "5f00f99c550a360506e23c8b91f7e29ba400088a732e3a061ece166440d04ef4", "release_id": "028", "repository_url": "https://github.com/JialongJiang/DSPIN", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_028", "title": "Repair control-referenced relative responses in a single-cell perturbation workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-028:v0.1.1@sha256:4c4ec965b94251ab9b163fe1294a4e863dc5a2b0a005dabb51dbaa5a5d6c95fe", "verifier_image_digest": "sha256:4c4ec965b94251ab9b163fe1294a4e863dc5a2b0a005dabb51dbaa5a5d6c95fe", "verifier_image_id": "sha256:4c4ec965b94251ab9b163fe1294a4e863dc5a2b0a005dabb51dbaa5a5d6c95fe", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-028:v0.1.1"}
{"base_commit": "fb0e7f522d714d76eec42f5fd428eb7942a11dde", "domain": "genomics-sequence-annotation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-029:v0.1.1@sha256:ef7e5c2b118cfb635fe2a38a96a3e74a8b8ccad4f45c4420a262224cde2aed3d", "environment_image_digest": "sha256:ef7e5c2b118cfb635fe2a38a96a3e74a8b8ccad4f45c4420a262224cde2aed3d", "environment_image_id": "sha256:ef7e5c2b118cfb635fe2a38a96a3e74a8b8ccad4f45c4420a262224cde2aed3d", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-029:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.rst", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "c77a56a3a0f491a8d8323bc49a7f61646abddac45c3db18dc37baa8d3722dc95", "release_id": "029", "repository_url": "https://github.com/biopython/biopython", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_029", "title": "Restore annotation equivalence after circular-record orientation normalization", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-029:v0.1.1@sha256:bf60c02145e60447a42aa0e8205c11851bafae01fb38da1969c8ca9697ab119f", "verifier_image_digest": "sha256:bf60c02145e60447a42aa0e8205c11851bafae01fb38da1969c8ca9697ab119f", "verifier_image_id": "sha256:bf60c02145e60447a42aa0e8205c11851bafae01fb38da1969c8ca9697ab119f", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-029:v0.1.1"}
{"base_commit": "585bb673c4aa222669c4b0d72ffeec3dbf092630", "domain": "crystallography-file-format-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-030:v0.1.1@sha256:0b58b97e18857fc5e3b937628024ab3bc13ba59952651b287ed6bd19c1ca11fa", "environment_image_digest": "sha256:0b58b97e18857fc5e3b937628024ab3bc13ba59952651b287ed6bd19c1ca11fa", "environment_image_id": "sha256:0b58b97e18857fc5e3b937628024ab3bc13ba59952651b287ed6bd19c1ca11fa", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-030:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "public_payload_sha256": "fe8a693f065061ef2c9dbeb378deabfb408a0b54cad15bb727f0dbfc6d7e05da", "release_id": "030", "repository_url": "https://github.com/materialsproject/pymatgen", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_030", "title": "Repair format-conformant SHELX/AIRSS .res export in a crystallographic IO workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-030:v0.1.1@sha256:a7a1ebc4f0d09c76072fd97d407d581348c92def2eb9cf4414cbca7a2d2175de", "verifier_image_digest": "sha256:a7a1ebc4f0d09c76072fd97d407d581348c92def2eb9cf4414cbca7a2d2175de", "verifier_image_id": "sha256:a7a1ebc4f0d09c76072fd97d407d581348c92def2eb9cf4414cbca7a2d2175de", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-030:v0.1.1"}
{"base_commit": "3b3f3afb0e46a6ac6b97e6ecfbc2414497ea9a3a", "domain": "neurophysiology-signal-processing", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-031:v0.1.1@sha256:0a7aa2348bab33d8e8d96876194c1cfe25e4bb8aa79bd2d39b2a0722a27daac2", "environment_image_digest": "sha256:0a7aa2348bab33d8e8d96876194c1cfe25e4bb8aa79bd2d39b2a0722a27daac2", "environment_image_id": "sha256:0a7aa2348bab33d8e8d96876194c1cfe25e4bb8aa79bd2d39b2a0722a27daac2", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-031:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "BSD-3-Clause; CC-BY-3.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "b04eeec751f5ffcf9dd8fd3e83d1d44be46e0a6085ba40d372492bb7f675a4e3", "public_payload_sha256": "b0883c2ad7370e00fae5d015cce43f8996f59f9f36cf0cbc1b0b441d7b5d90fb", "release_id": "031", "repository_url": "https://github.com/mne-tools/mne-python", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_031", "title": "Restore documented average-reference semantics for mixed-modality recordings", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-031:v0.1.1@sha256:76dd16524e2f8d46d8a4dc15f04b0c00d856be316fe9480271332ae20cac59f6", "verifier_image_digest": "sha256:76dd16524e2f8d46d8a4dc15f04b0c00d856be316fe9480271332ae20cac59f6", "verifier_image_id": "sha256:76dd16524e2f8d46d8a4dc15f04b0c00d856be316fe9480271332ae20cac59f6", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-031:v0.1.1"}
{"base_commit": "d2f76949b3ccac1139f0a0a0d1459aa47e2f0a98", "domain": "molecular-simulation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-032:v0.1.1@sha256:f7bbb41b0cb019c6785faf01ee02b71efef87ade2d96f78673157090b2b70c11", "environment_image_digest": "sha256:f7bbb41b0cb019c6785faf01ee02b71efef87ade2d96f78673157090b2b70c11", "environment_image_id": "sha256:f7bbb41b0cb019c6785faf01ee02b71efef87ade2d96f78673157090b2b70c11", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-032:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "license.rst", "material_license": "MIT; MIT AND LGPL-family AND BSD-3-Clause", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "a43f622287ae0e599204db58fb15d4c22e33975bd9609639356586f1126a89aa", "public_payload_sha256": "60338d260fc28a955f702fe04a9a76487e8ef6296fea7e885c9f75bf132c8f3b", "release_id": "032", "repository_url": "https://github.com/openmm/openmm", "restricted_license": true, "restricted_reason": "The OpenMM source snapshot includes LGPL-covered CUDA and OpenCL platform components and therefore requires explicit restricted-license opt-in.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT AND LGPL-family AND BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_032", "title": "Repair an inconsistent peptide energy after topology import", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-032:v0.1.1@sha256:c75faed022ffcf7321fcfc415227da35e38287acd1304c3cdf6fa487f6b8c2dd", "verifier_image_digest": "sha256:c75faed022ffcf7321fcfc415227da35e38287acd1304c3cdf6fa487f6b8c2dd", "verifier_image_id": "sha256:c75faed022ffcf7321fcfc415227da35e38287acd1304c3cdf6fa487f6b8c2dd", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-032:v0.1.1"}
{"base_commit": "802cd37e9dc6abb52f30d84bb422b6ee15493fc9", "domain": "periodic-electronic-structure", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-033:v0.1.1@sha256:197e982f57b296e787d46cf34996907450e455aee4d3fab0602f6dc24bff6143", "environment_image_digest": "sha256:197e982f57b296e787d46cf34996907450e455aee4d3fab0602f6dc24bff6143", "environment_image_id": "sha256:197e982f57b296e787d46cf34996907450e455aee4d3fab0602f6dc24bff6143", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-033:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@802cd37e9dc6abb52f30d84bb422b6ee15493fc9", "material_license": "Apache-2.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "82da89147b9de73d02954a5589901714c78986e8fb1deeae9d8e3c636c92f7be", "public_payload_sha256": "070857cd34ba31641aded3b53ae1502eb1406a016c08121b4635b8df80cdd586", "release_id": "033", "repository_url": "https://github.com/pyscf/pyscf", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_033", "title": "Repair inconsistent energies across equivalent periodic representations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-033:v0.1.1@sha256:6dc7b560ea513f6160f7c57f10d097acc966df297e37e71f466e132810369295", "verifier_image_digest": "sha256:6dc7b560ea513f6160f7c57f10d097acc966df297e37e71f466e132810369295", "verifier_image_id": "sha256:6dc7b560ea513f6160f7c57f10d097acc966df297e37e71f466e132810369295", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-033:v0.1.1"}
{"base_commit": "56d78e1acbdc9c1493caef17a34777931430f3bf", "domain": "stochastic-numerical-analysis", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-034:v0.1.1@sha256:fa45aacfb4bbf402fbd7597ca767d61065cf767a35e9c457f708bb024e46a29f", "environment_image_digest": "sha256:fa45aacfb4bbf402fbd7597ca767d61065cf767a35e9c457f708bb024e46a29f", "environment_image_id": "sha256:fa45aacfb4bbf402fbd7597ca767d61065cf767a35e9c457f708bb024e46a29f", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-034:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "Apache-2.0; CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "f165a9cd5a3804fded776a27a284ba9e6458bd6f0fc281b5de5541181a7f30db", "public_payload_sha256": "13493379beb9f833e2a1ce4739d2ca74b89c005aa12e802601a6c58f1203b6c6", "release_id": "034", "repository_url": "https://github.com/patrick-kidger/diffrax", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_034", "title": "Repair an inconsistent stochastic trajectory calculation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-034:v0.1.1@sha256:05bcfc247e7ddf648bb2c176a6a51e0044fe3e262fb1520291c13384074fdaa7", "verifier_image_digest": "sha256:05bcfc247e7ddf648bb2c176a6a51e0044fe3e262fb1520291c13384074fdaa7", "verifier_image_id": "sha256:05bcfc247e7ddf648bb2c176a6a51e0044fe3e262fb1520291c13384074fdaa7", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-034:v0.1.1"}
{"base_commit": "c4e7f1146556f4b038bfbfc0912ac3843e844c55", "domain": "numerical-analysis-and-chemical-kinetics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-035:v0.1.1@sha256:9d074595d6ab4385a00875330b4b1fa44153bcfc3e20f4fb7b93005582556bed", "environment_image_digest": "sha256:9d074595d6ab4385a00875330b4b1fa44153bcfc3e20f4fb7b93005582556bed", "environment_image_id": "sha256:9d074595d6ab4385a00875330b4b1fa44153bcfc3e20f4fb7b93005582556bed", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-035:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "restricted-materials", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "BSD-2-Clause; BSD-3-Clause; LicenseRef-US-Government-Publication", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "32ef8eed974831bd603273c8e83ae05fa07cf917096ee7c44821f74ffbe6b457", "public_payload_sha256": "59de791822368383ceb7af7bbf1167f13a003e19b06e6d2b5075b0c80f5c5fe7", "release_id": "035", "repository_url": "https://github.com/scipy/scipy", "restricted_license": true, "restricted_reason": "The NASA ODEPACK report is retained for reproducibility, but its public-domain or commercial redistribution status is not represented by an explicit standard license grant; commercial users must opt in after their own review.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_035", "title": "Repair an incomplete stiff-kinetics campaign", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-035:v0.1.1@sha256:3f5829a8aac0f18cc8716f569d96154613a115e082be984153eedf0e81afdc8a", "verifier_image_digest": "sha256:3f5829a8aac0f18cc8716f569d96154613a115e082be984153eedf0e81afdc8a", "verifier_image_id": "sha256:3f5829a8aac0f18cc8716f569d96154613a115e082be984153eedf0e81afdc8a", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-035:v0.1.1"}
{"base_commit": "439ea290f9a75c3cbd66d79333fed475f92aeb00", "domain": "computational-oceanography-and-spherical-geometry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-036:v0.1.1@sha256:bde81a3c141fddd89bb39021eb1ac122021f63e81c99aadef61a1c1e86ac82e4", "environment_image_digest": "sha256:bde81a3c141fddd89bb39021eb1ac122021f63e81c99aadef61a1c1e86ac82e4", "environment_image_id": "sha256:bde81a3c141fddd89bb39021eb1ac122021f63e81c99aadef61a1c1e86ac82e4", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-036:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "4755047fd73d5c730562078d025169f820967fe96b30cd369100c9c74ead3bf8", "public_payload_sha256": "269b06c6266cd7ec7845139ea025286343c4f9fbe7b3116be37a204cdacad1c4", "release_id": "036", "repository_url": "https://github.com/Parcels-code/Parcels", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_036", "title": "Repair inconsistent sampling on a spherical curvilinear ocean grid", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-036:v0.1.1@sha256:97009f66b48e65e82d8e706d3e07eadded40d4918020554f7a9886708786dd69", "verifier_image_digest": "sha256:97009f66b48e65e82d8e706d3e07eadded40d4918020554f7a9886708786dd69", "verifier_image_id": "sha256:97009f66b48e65e82d8e706d3e07eadded40d4918020554f7a9886708786dd69", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-036:v0.1.1"}
{"base_commit": "5d10c5b8bb09576e24e9d316da1019fb909d7d32", "domain": "medical-imaging", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-037:v0.1.1@sha256:d56fc142c29e55c2da1bbb2a3da5afda71387fd8dd092742882d7a7311687b71", "environment_image_digest": "sha256:d56fc142c29e55c2da1bbb2a3da5afda71387fd8dd092742882d7a7311687b71", "environment_image_id": "sha256:d56fc142c29e55c2da1bbb2a3da5afda71387fd8dd092742882d7a7311687b71", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-037:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "MIT; MIT AND BSD-3-Clause", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "acb0c4de1a255bde515f780d34c7a0585d488b13032ef4bed6e78fab84f60f0b", "public_payload_sha256": "525e11dbf5bfc048c2efde3fd15fe6993ba36cf2dd8a1a1d3afb9c320baab674", "release_id": "037", "repository_url": "https://github.com/nipy/nibabel", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT AND BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_037", "title": "Repair an inconsistent multiframe MR reconstruction", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-037:v0.1.1@sha256:c796741230bb4ab445d45895f095d69787bd4539b73918856d1ad79488bac7e3", "verifier_image_digest": "sha256:c796741230bb4ab445d45895f095d69787bd4539b73918856d1ad79488bac7e3", "verifier_image_id": "sha256:c796741230bb4ab445d45895f095d69787bd4539b73918856d1ad79488bac7e3", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-037:v0.1.1"}
{"base_commit": "", "domain": "computational-crystallography-and-materials-symmetry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-038:v0.1.1@sha256:7a3e4ccf5364e434c5a3d4710e2016df66ef5db3cf063d0249574c59143dd793", "environment_image_digest": "sha256:7a3e4ccf5364e434c5a3d4710e2016df66ef5db3cf063d0249574c59143dd793", "environment_image_id": "sha256:7a3e4ccf5364e434c5a3d4710e2016df66ef5db3cf063d0249574c59143dd793", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-038:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "c", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "BSD-3-Clause; CC-BY-4.0; CC0-1.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "cde0e5d6b19a6be1907d83aceadce31d5eabdb8386ce8b7fbfaabc08f8b0ebf2", "public_payload_sha256": "d770bd89cde0d7ebe7ef628d9f4c5f28fe4267abef25159f14379e03a786ce28", "release_id": "038", "repository_url": "https://github.com/spglib/spglib", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_038", "title": "Repair inconsistent crystal classification across equivalent representations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-038:v0.1.1@sha256:4bb7c29ed433773c37de68bad0e425e75710b6709e0beec1b63f0f3691539643", "verifier_image_digest": "sha256:4bb7c29ed433773c37de68bad0e425e75710b6709e0beec1b63f0f3691539643", "verifier_image_id": "sha256:4bb7c29ed433773c37de68bad0e425e75710b6709e0beec1b63f0f3691539643", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-038:v0.1.1"}
{"base_commit": "546bc11054cff5e12808c7122b3e8b38f1ef555f", "domain": "earth-surface-dynamics-and-river-sediment-transport", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-039:v0.1.1@sha256:8e1428ce9adff057ad094b79fa0a1b7e863d8a0a9925247cf509c0b88b830f15", "environment_image_digest": "sha256:8e1428ce9adff057ad094b79fa0a1b7e863d8a0a9925247cf509c0b88b830f15", "environment_image_id": "sha256:8e1428ce9adff057ad094b79fa0a1b7e863d8a0a9925247cf509c0b88b830f15", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-039:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "87f8d5c4cb8e737bccacf5718560d2395d37ca9721a6354d211546d7b71d8b3d", "public_payload_sha256": "fa7b5edfc79afde5d113788e3d4eea5c80bb684cd131834ba61c477cdeef2539", "release_id": "039", "repository_url": "https://github.com/landlab/landlab", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_039", "title": "Repair a river-network sediment transport calculation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-039:v0.1.1@sha256:1533cb3577d15acdc7fd3b1f755f8c4ec80fbb528b7bcb6bcf918c6559f20e4a", "verifier_image_digest": "sha256:1533cb3577d15acdc7fd3b1f755f8c4ec80fbb528b7bcb6bcf918c6559f20e4a", "verifier_image_id": "sha256:1533cb3577d15acdc7fd3b1f755f8c4ec80fbb528b7bcb6bcf918c6559f20e4a", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-039:v0.1.1"}
{"base_commit": "3cc6605c54b0f6062c1a139ece2ecf69cddc829", "domain": "computational-electromagnetics-and-geophysical-forward-modeling", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-040:v0.1.1@sha256:b08140e893ca136c31d83c2afc20b073a950a985dfeaf77c3443674dea1fb245", "environment_image_digest": "sha256:b08140e893ca136c31d83c2afc20b073a950a985dfeaf77c3443674dea1fb245", "environment_image_id": "sha256:b08140e893ca136c31d83c2afc20b073a950a985dfeaf77c3443674dea1fb245", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-040:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "18dd16f868317598b365a29daaf8266ade1e05ce665379fc8b98e18bc568c9e0", "public_payload_sha256": "0dda4607fc677d002313ced33a5bf17c4721716fe9e640b9a713ebfa655ca4a6", "release_id": "040", "repository_url": "https://github.com/simpeg/simpeg", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_040", "title": "Restore consistent magnetic-dipole electromagnetic predictions", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-040:v0.1.1@sha256:65832254b48e4b1777a7d1d07680a2a870de87c697b47ff8d0c27a516f95ad46", "verifier_image_digest": "sha256:65832254b48e4b1777a7d1d07680a2a870de87c697b47ff8d0c27a516f95ad46", "verifier_image_id": "sha256:65832254b48e4b1777a7d1d07680a2a870de87c697b47ff8d0c27a516f95ad46", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-040:v0.1.1"}
{"base_commit": "470d13491dd2c2a9440b3c657af33373ca8d47c1", "domain": "space-physics-coordinate-systems", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-041:v0.1.1@sha256:37b558bb6c922ebc1e934902b60d7d8d4779e0b0bb261c94a7374079ab64b23d", "environment_image_digest": "sha256:37b558bb6c922ebc1e934902b60d7d8d4779e0b0bb261c94a7374079ab64b23d", "environment_image_id": "sha256:37b558bb6c922ebc1e934902b60d7d8d4779e0b0bb261c94a7374079ab64b23d", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-041:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "BSD-2-Clause; CC-BY-3.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "d730adf2dafa71100b7ecab539721131b1158fb83c7cddee2f0b95f2cff5d6ed", "public_payload_sha256": "beb96a14326679e2ff694d6cbd7af3867734b6d00d83609c1ab40cbc77c9de48", "release_id": "041", "repository_url": "https://github.com/sunpy/sunpy", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-2-Clause", "status": "dockerhub-published", "task_path": "tasks/task_041", "title": "Repair an inconsistent near-Earth vector conversion", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-041:v0.1.1@sha256:89c3b061bcb5d19a2b28722e4c8a1a5c2435e8641d4cdc2f2ffbd565bc48ff10", "verifier_image_digest": "sha256:89c3b061bcb5d19a2b28722e4c8a1a5c2435e8641d4cdc2f2ffbd565bc48ff10", "verifier_image_id": "sha256:89c3b061bcb5d19a2b28722e4c8a1a5c2435e8641d4cdc2f2ffbd565bc48ff10", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-041:v0.1.1"}
{"base_commit": "c961a1507a83b9dab24ccce12ab92a53b30359d7", "domain": "solar-physics-scientific-data-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-042:v0.1.1@sha256:e24e50089bf65cd0f7c88ef150c571446734e71f07990016584bbc39a9c7bebc", "environment_image_digest": "sha256:e24e50089bf65cd0f7c88ef150c571446734e71f07990016584bbc39a9c7bebc", "environment_image_id": "sha256:e24e50089bf65cd0f7c88ef150c571446734e71f07990016584bbc39a9c7bebc", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-042:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "BSD-2-Clause; BSD-3-Clause; CC-BY-3.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "9aa2c24653f08c06f88cbeaaf0537b5fd1bc0c184ced600d54a6cc9e8bd1418c", "public_payload_sha256": "3a136f5021626770b12d3bee550b08805195dffbfe5dd391b107f97bb61adcca", "release_id": "042", "repository_url": "https://github.com/sunpy/sunpy", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-2-Clause", "status": "dockerhub-published", "task_path": "tasks/task_042", "title": "Repair an inconsistent solar-coordinate archive workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-042:v0.1.1@sha256:2d3c7dba05b8ca04b80900872baa59a5f3bc42d765e80ed58aa917bf0126c512", "verifier_image_digest": "sha256:2d3c7dba05b8ca04b80900872baa59a5f3bc42d765e80ed58aa917bf0126c512", "verifier_image_id": "sha256:2d3c7dba05b8ca04b80900872baa59a5f3bc42d765e80ed58aa917bf0126c512", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-042:v0.1.1"}
{"base_commit": "f2360a52bc77ec917aa07ce0cf6128dc7687ea64", "domain": "porous-media-image-analysis", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-043:v0.1.1@sha256:1207c3ad5330252d5696310459258a043adf59491b41fb27ddc0e0d6fd659e8e", "environment_image_digest": "sha256:1207c3ad5330252d5696310459258a043adf59491b41fb27ddc0e0d6fd659e8e", "environment_image_id": "sha256:1207c3ad5330252d5696310459258a043adf59491b41fb27ddc0e0d6fd659e8e", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-043:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "bcd5dd8b8c7bb4aeccaa91f8e56d0b0cacb3d51c3fa226e2e95c4ee369bb017a", "public_payload_sha256": "30e2dc25b63a8bffbdcfbe59c9ddc617a30478957a7eba9f4b0ff624dfc64bd1", "release_id": "043", "repository_url": "https://github.com/PMEAL/porespy", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_043", "title": "Repair an inconsistent porous-volume characterization", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-043:v0.1.1@sha256:84e2a692b8b83060583de8fca377a153136ba35bd01e40d4ff4e61fe116e2472", "verifier_image_digest": "sha256:84e2a692b8b83060583de8fca377a153136ba35bd01e40d4ff4e61fe116e2472", "verifier_image_id": "sha256:84e2a692b8b83060583de8fca377a153136ba35bd01e40d4ff4e61fe116e2472", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-043:v0.1.1"}
{"base_commit": "a42d7a92dd9a2c63240c8ccb6f240e5c3c42de46", "domain": "electrochemical-battery-modeling", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-044:v0.1.1@sha256:83a59d87af5edf2d56822d5bbe902c10a9afdc7afbb11f70903b0de99719335a", "environment_image_digest": "sha256:83a59d87af5edf2d56822d5bbe902c10a9afdc7afbb11f70903b0de99719335a", "environment_image_id": "sha256:83a59d87af5edf2d56822d5bbe902c10a9afdc7afbb11f70903b0de99719335a", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-044:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "BSD-3-Clause; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "e2b4e018508a5d1fc30c97dc278fe89962d811608494c1c9796a01e93b7108c0", "public_payload_sha256": "04feef6107c02cd8411cc3c572cc7920d0d6f393fccaca8db4e514c470098d4a", "release_id": "044", "repository_url": "https://github.com/pybamm-team/PyBaMM", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_044", "title": "Repair inconsistent lithium-ion discharge predictions", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-044:v0.1.1@sha256:71ce7ba80a7fa8e30f073a714ed124130925d8fc6945760d3b28e176bdba2973", "verifier_image_digest": "sha256:71ce7ba80a7fa8e30f073a714ed124130925d8fc6945760d3b28e176bdba2973", "verifier_image_id": "sha256:71ce7ba80a7fa8e30f073a714ed124130925d8fc6945760d3b28e176bdba2973", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-044:v0.1.1"}
{"base_commit": "3831b46accbff35f06e4ed3831600d71d5d8da18", "domain": "computational-oceanography-finite-volume-grids", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-045:v0.1.1@sha256:7c1a6d7c324fb06b666139cc162487e81c848774f8392ff857ea3130c8bdf145", "environment_image_digest": "sha256:7c1a6d7c324fb06b666139cc162487e81c848774f8392ff857ea3130c8bdf145", "environment_image_id": "sha256:7c1a6d7c324fb06b666139cc162487e81c848774f8392ff857ea3130c8bdf145", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-045:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "manifests/materials.jsonl and retained upstream notices", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "e1df72bc136f6191328e4b4526e844e2053bba0345f780c1166f356c7f046254", "public_payload_sha256": "409b1fdef4d7b646748ecf16b5afcca323619fd843d0c33a8b45373c864bc325", "release_id": "045", "repository_url": "https://github.com/xgcm/xgcm", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_045", "title": "Repair inconsistent finite-volume operations on a connected multi-face grid", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-045:v0.1.1@sha256:8f1017124bd8c6ff303864a9f681042f38a68c6026620b1ddc187bfba8555525", "verifier_image_digest": "sha256:8f1017124bd8c6ff303864a9f681042f38a68c6026620b1ddc187bfba8555525", "verifier_image_id": "sha256:8f1017124bd8c6ff303864a9f681042f38a68c6026620b1ddc187bfba8555525", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-045:v0.1.1"}
{"base_commit": "79b8f9bb9d122bd0176bb37f48f0fd4926eb9afb", "domain": "astrophysical-xray-spectral-timing", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-046:v0.1.1@sha256:9720d0e8ab177e9c0088d25a097537723e44dbc1cf62761243162f19a75ab3af", "environment_image_digest": "sha256:9720d0e8ab177e9c0088d25a097537723e44dbc1cf62761243162f19a75ab3af", "environment_image_id": "sha256:9720d0e8ab177e9c0088d25a097537723e44dbc1cf62761243162f19a75ab3af", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-046:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.rst", "material_license": "CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "fb5ce52316b37200b1cecae3c497aaf8cc698f7449797aae85102ef4163b32cd", "public_payload_sha256": "f2ef4efa4831e06d2562ca991fefa2565f59ae46f0a01ebf3023222dd86e65a6", "release_id": "046", "repository_url": "https://github.com/StingraySoftware/stingray", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_046", "title": "Repair an inconsistent X-ray spectral-timing analysis", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-046:v0.1.1@sha256:272c4cfe4cc4bc671ea369eeb6bf97bdc117cf5332c3f4b1468ab20364c9cb07", "verifier_image_digest": "sha256:272c4cfe4cc4bc671ea369eeb6bf97bdc117cf5332c3f4b1468ab20364c9cb07", "verifier_image_id": "sha256:272c4cfe4cc4bc671ea369eeb6bf97bdc117cf5332c3f4b1468ab20364c9cb07", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-046:v0.1.1"}
{"base_commit": "a6dae181dbcf76fc738fc7fbc03d7de0a6c22634", "domain": "microwave-network-analysis", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-047:v0.1.1@sha256:72115b285908d59e5313c5730e7c2f5b9c78c2342064962f66eccdc6514b2fca", "environment_image_digest": "sha256:72115b285908d59e5313c5730e7c2f5b9c78c2342064962f66eccdc6514b2fca", "environment_image_id": "sha256:72115b285908d59e5313c5730e7c2f5b9c78c2342064962f66eccdc6514b2fca", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-047:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "BSD-3-Clause; LicenseRef-NIST-US-Public-Domain-and-Worldwide-Reprint-Permission", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "dc522d02a3bfe41fdce0651525b3bc51ead8dce3296b2c583084fd64839ffb24", "public_payload_sha256": "e82919086e808921565f7d30639962652952147ee8a748c5f215dc87291f2da9", "release_id": "047", "repository_url": "https://github.com/scikit-rf/scikit-rf", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_047", "title": "Repair an inconsistent broadband microwave composite", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-047:v0.1.1@sha256:6255287669b4711882fdd9c817e94e31ba63f6cbc228a2469763f45b3019144b", "verifier_image_digest": "sha256:6255287669b4711882fdd9c817e94e31ba63f6cbc228a2469763f45b3019144b", "verifier_image_id": "sha256:6255287669b4711882fdd9c817e94e31ba63f6cbc228a2469763f45b3019144b", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-047:v0.1.1"}
{"base_commit": "50389503f126ea6f9e40947c215bd857bcfbd9de", "domain": "computational-thermodynamics-calphad", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-048:v0.1.1@sha256:7000ceeb77adb2c980d318a30ff17bdbebaaad19ce0bb3f4372a770a02c26346", "environment_image_digest": "sha256:7000ceeb77adb2c980d318a30ff17bdbebaaad19ce0bb3f4372a770a02c26346", "environment_image_id": "sha256:7000ceeb77adb2c980d318a30ff17bdbebaaad19ce0bb3f4372a770a02c26346", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-048:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "9093b7c978d3f58fdfc199cb70741135938c393e8266a9cbe454f1b72a017d30", "public_payload_sha256": "976927397d08cf492ca124439053b1da678e6c7a261c4074ad6f7622069d194c", "release_id": "048", "repository_url": "https://github.com/pycalphad/pycalphad", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_048", "title": "Repair an inconsistent alloy equilibrium assessment", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-048:v0.1.1@sha256:670f242d783782ed07312104f888007fdfa136952eb46941c065cfb4b5d9eb14", "verifier_image_digest": "sha256:670f242d783782ed07312104f888007fdfa136952eb46941c065cfb4b5d9eb14", "verifier_image_id": "sha256:670f242d783782ed07312104f888007fdfa136952eb46941c065cfb4b5d9eb14", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-048:v0.1.1"}
{"base_commit": "a9f8256c1b4b48ac73f3df35b3e570993501b333", "domain": "finite-difference-stochastic-partial-differential-equations", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-049:v0.1.1@sha256:08749a092307b212a07d9f05b2edb2d74478b32f3d6d4e59bee97f22fe1fa3c1", "environment_image_digest": "sha256:08749a092307b212a07d9f05b2edb2d74478b32f3d6d4e59bee97f22fe1fa3c1", "environment_image_id": "sha256:08749a092307b212a07d9f05b2edb2d74478b32f3d6d4e59bee97f22fe1fa3c1", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-049:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "ae153bd68ea5352c49651111c1c225e8f7ccc5fc0c3440f1942218da873b339f", "public_payload_sha256": "1f8c10aeb2fa8a71d3384e7096729de509e81cbcc11a05c11546c10077e52c06", "release_id": "049", "repository_url": "https://github.com/zwicker-group/py-pde", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_049", "title": "Restore consistent stochastic-field behavior on nonuniform grids", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-049:v0.1.1@sha256:ba7d3a2168c254fda002f5263c1e7d965577633f0473184e212743416a1d77fb", "verifier_image_digest": "sha256:ba7d3a2168c254fda002f5263c1e7d965577633f0473184e212743416a1d77fb", "verifier_image_id": "sha256:ba7d3a2168c254fda002f5263c1e7d965577633f0473184e212743416a1d77fb", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-049:v0.1.1"}
{"base_commit": "79594e405ac72da908cdd7a1058911afc256c483", "domain": "quantum-information-many-body-tensor-networks", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-050:v0.1.1@sha256:09a81d661864341accf7eeadb063ca71c117e25cb86f5e2dc822964374cb8a78", "environment_image_digest": "sha256:09a81d661864341accf7eeadb063ca71c117e25cb86f5e2dc822964374cb8a78", "environment_image_id": "sha256:09a81d661864341accf7eeadb063ca71c117e25cb86f5e2dc822964374cb8a78", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-050:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "Apache-2.0; CC-BY-4.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "c63b58bb1182776e8577921993d028a074627bb229e4d159ffb745884463a516", "public_payload_sha256": "52919276a341c13deaecf84de42a7701c9fa9c2f0bb58a3253fce75721feef27", "release_id": "050", "repository_url": "https://github.com/jcmgray/quimb", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_050", "title": "Repair an inconsistent tensor-network state calculation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-050:v0.1.1@sha256:329b4cefbac68b9fff040c801b61c9edc46971f6378547731630f50d353d6a48", "verifier_image_digest": "sha256:329b4cefbac68b9fff040c801b61c9edc46971f6378547731630f50d353d6a48", "verifier_image_id": "sha256:329b4cefbac68b9fff040c801b61c9edc46971f6378547731630f50d353d6a48", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-050:v0.1.1"}
{"base_commit": "7f7d91474509acb597071eb789661b1f0cc304ca", "domain": "planetary-geodesy-and-geomagnetism", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-fortran-task-051:v0.1.0@sha256:8235525555c16d48f6e12019ba6239fc99569358183a444cb0251b72dfd99de4", "environment_image_digest": "sha256:8235525555c16d48f6e12019ba6239fc99569358183a444cb0251b72dfd99de4", "environment_image_id": "sha256:8235525555c16d48f6e12019ba6239fc99569358183a444cb0251b72dfd99de4", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-fortran-task-051:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "fortran", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "BSD-3-Clause", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "4386eda57f7e1e22e6cca9c2cc037a969777a74295eb4dd7c57d8b9c2228b2e9", "public_payload_sha256": "e12cdd178e91e4970a775d1426972061c0ab4548b2b3b37c7093671aa51b8362", "release_id": "051", "repository_url": "https://github.com/SHTOOLS/SHTOOLS", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_051", "title": "Repair an inconsistent planetary gradient-tensor calculation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-fortran-task-051:v0.1.0@sha256:cc4ffda89baf3ef1fed6903ff06b194b1ef2f992413574aa6032451e09e653fb", "verifier_image_digest": "sha256:cc4ffda89baf3ef1fed6903ff06b194b1ef2f992413574aa6032451e09e653fb", "verifier_image_id": "sha256:cc4ffda89baf3ef1fed6903ff06b194b1ef2f992413574aa6032451e09e653fb", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-fortran-task-051:v0.1.0"}
{"base_commit": "11e5c6ae26207a60e223d46473ac364b352ac982", "domain": "computational-materials-finite-volume-pde", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-052:v0.1.1@sha256:0d308a88c17c4ee22a73f9a0099eef6f91d71ac67802e1f2c84164a990f7d4b1", "environment_image_digest": "sha256:0d308a88c17c4ee22a73f9a0099eef6f91d71ac67802e1f2c84164a990f7d4b1", "environment_image_id": "sha256:0d308a88c17c4ee22a73f9a0099eef6f91d71ac67802e1f2c84164a990f7d4b1", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-052:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "source/LICENSE.rst", "material_license": "LicenseRef-NIST-US-Public-Domain-and-Worldwide-Reprint-Permission; NIST-PD-fallback", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "5280107b19f5194bc7d2420757586110ade8425ed6dc7c68c5d6e52e3948bfad", "public_payload_sha256": "00da7b75f004dccce49efebd3092cd7a7a996acfcf8af9f5ccf8cc6a15f52616", "release_id": "052", "repository_url": "https://github.com/usnistgov/fipy", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "NIST-PD-fallback", "status": "dockerhub-published", "task_path": "tasks/task_052", "title": "Restore a nonuniform finite-volume phase-field workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-052:v0.1.1@sha256:6f57ba5eb80547a9be07d6beb7ae5671185492774b45cbacd216a7a15b0e8b3c", "verifier_image_digest": "sha256:6f57ba5eb80547a9be07d6beb7ae5671185492774b45cbacd216a7a15b0e8b3c", "verifier_image_id": "sha256:6f57ba5eb80547a9be07d6beb7ae5671185492774b45cbacd216a7a15b0e8b3c", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-052:v0.1.1"}
{"base_commit": "18daff1d8b26002b02de526cc19b92a9a4907f89", "domain": "medical-image-segmentation-geometry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-053:v0.1.1@sha256:368abf8c85d39c21041f86669de6193e09c14ee439bfd1946d8d79d3e3655bf8", "environment_image_digest": "sha256:368abf8c85d39c21041f86669de6193e09c14ee439bfd1946d8d79d3e3655bf8", "environment_image_id": "sha256:368abf8c85d39c21041f86669de6193e09c14ee439bfd1946d8d79d3e3655bf8", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-053:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@18daff1d8b26002b02de526cc19b92a9a4907f89", "material_license": "Apache-2.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "7706c9274cdba7a2e13d88bef4a39fda71f3fe0b00905a41f42b80eaf466203b", "public_payload_sha256": "2f51cdd846bb96604a4d116a8b4c70aec26d5a5cf51be1c3e4455b7d552184fd", "release_id": "053", "repository_url": "https://github.com/Project-MONAI/MONAI", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_053", "title": "Repair a representation-dependent physical surface Dice workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-053:v0.1.1@sha256:4b7abdcd97eba26396cb2266fa96840b46072599989a98c201c2ddb6516074d3", "verifier_image_digest": "sha256:4b7abdcd97eba26396cb2266fa96840b46072599989a98c201c2ddb6516074d3", "verifier_image_id": "sha256:4b7abdcd97eba26396cb2266fa96840b46072599989a98c201c2ddb6516074d3", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-053:v0.1.1"}
{"base_commit": "9f27ba89d8c485e6a2fa2db4756e3fe3aec05151", "domain": "mass-spectrometry-spectral-similarity", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-054:v0.1.1@sha256:757aa71982f2d2694a3c99cc89e9127c18d9a1afed4ae88c89bcfb741339101f", "environment_image_digest": "sha256:757aa71982f2d2694a3c99cc89e9127c18d9a1afed4ae88c89bcfb741339101f", "environment_image_id": "sha256:757aa71982f2d2694a3c99cc89e9127c18d9a1afed4ae88c89bcfb741339101f", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-054:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "Apache-2.0; CC-BY-4.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "03eef73a9942301ea5e43245d7ac6060640bf7c09359f3f596e8b37db07b7db4", "public_payload_sha256": "c2c21f52aa16aa43ca1823531c017161384825d8699e69b254c52e3070d0548a", "release_id": "054", "repository_url": "https://github.com/matchms/matchms", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_054", "title": "Repair an inconsistent tandem-mass spectral similarity workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-054:v0.1.1@sha256:9b8eb137609838bf28828e687f9d0814b79c50f67e47fac66478944a2ff5572c", "verifier_image_digest": "sha256:9b8eb137609838bf28828e687f9d0814b79c50f67e47fac66478944a2ff5572c", "verifier_image_id": "sha256:9b8eb137609838bf28828e687f9d0814b79c50f67e47fac66478944a2ff5572c", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-054:v0.1.1"}
{"base_commit": "0613ba1ba86fd7ae79e9d89c8ffd24004a891aee", "domain": "astronomical-spectroscopy", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-055:v0.1.1@sha256:045c73eff4c5b1ecb95f4e77e9e676e231a2873ff81fc5dee214bcb1d00b5933", "environment_image_digest": "sha256:045c73eff4c5b1ecb95f4e77e9e676e231a2873ff81fc5dee214bcb1d00b5933", "environment_image_id": "sha256:045c73eff4c5b1ecb95f4e77e9e676e231a2873ff81fc5dee214bcb1d00b5933", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-055:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.rst", "material_license": "BSD-3-Clause", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "02a2aef12aff642444e70cd640a2ae2121c2f5ad99ddab2e94932b60655be4a8", "public_payload_sha256": "3aeb7e8888d22a149778213fb70380ce80f4d21bd86e4584f7769895976e19ef", "release_id": "055", "repository_url": "https://github.com/astropy/specutils", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_055", "title": "Restore a scientific template-comparison workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-055:v0.1.1@sha256:3fcc630e3894beeac75efb4a0af160c6d174432a0eccfa2f14432fad8890f97d", "verifier_image_digest": "sha256:3fcc630e3894beeac75efb4a0af160c6d174432a0eccfa2f14432fad8890f97d", "verifier_image_id": "sha256:3fcc630e3894beeac75efb4a0af160c6d174432a0eccfa2f14432fad8890f97d", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-055:v0.1.1"}
{"base_commit": "0583b33091b07229abe2027bccdc596ba3c5033b0", "domain": "astrodynamics-and-orbital-mechanics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-056:v0.1.1@sha256:b30ad2201f576741d29e175928f89a3326113b4aac13fdf0732c5db64ba7333d", "environment_image_digest": "sha256:b30ad2201f576741d29e175928f89a3326113b4aac13fdf0732c5db64ba7333d", "environment_image_id": "sha256:b30ad2201f576741d29e175928f89a3326113b4aac13fdf0732c5db64ba7333d", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-056:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "COPYING", "material_license": "CC-BY-3.0; CC-BY-SA-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "3c0c7fc8f3d39ce2e51f40e009ed1bb6f5f130fc9f71636eb1ad461e08b8ffaa", "public_payload_sha256": "144a6f4df79aec52c1dc4291556e53ad8baf197b46e248659d6e98dcd6cf04f2", "release_id": "056", "repository_url": "https://github.com/poliastro/poliastro", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_056", "title": "Repair a physically inconsistent orbital history export", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-056:v0.1.1@sha256:a98a8c6a3139056d26e98222b863448e79379a0c988e9812ea69a76e39a65072", "verifier_image_digest": "sha256:a98a8c6a3139056d26e98222b863448e79379a0c988e9812ea69a76e39a65072", "verifier_image_id": "sha256:a98a8c6a3139056d26e98222b863448e79379a0c988e9812ea69a76e39a65072", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-056:v0.1.1"}
{"base_commit": "b963d4f01290fef66cca714e4a53f4891096b69a", "domain": "molecular-dynamics-trajectory-analysis", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-057:v0.1.1@sha256:78e4c7be579121b96cd0aa08686f45886030c5ce4883fe24fc785d6766dc1a8d", "environment_image_digest": "sha256:78e4c7be579121b96cd0aa08686f45886030c5ce4883fe24fc785d6766dc1a8d", "environment_image_id": "sha256:78e4c7be579121b96cd0aa08686f45886030c5ce4883fe24fc785d6766dc1a8d", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-057:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "material_license": "LGPL-2.1-family", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "85f053e1f9b99d7ce2a02d9f57b0c88a7b5d851e66a6d93c4c14a884b0c86099", "public_payload_sha256": "eb03dbe285ebd8c27960ace18eed00b3dcf23274440180a598ad578ba05e6502", "release_id": "057", "repository_url": "https://github.com/mdtraj/mdtraj", "restricted_license": true, "restricted_reason": "LGPL-2.1-covered MDTraj source and the complete upstream manual require explicit restricted-license opt-in.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-2.1-family", "status": "dockerhub-published", "task_path": "tasks/task_057", "title": "Investigate a periodic trajectory-processing anomaly", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-057:v0.1.1@sha256:1d75dca821fc4db5d8aa24f38b393e6c17703c69e1a20ce256a64b908fe7a60f", "verifier_image_digest": "sha256:1d75dca821fc4db5d8aa24f38b393e6c17703c69e1a20ce256a64b908fe7a60f", "verifier_image_id": "sha256:1d75dca821fc4db5d8aa24f38b393e6c17703c69e1a20ce256a64b908fe7a60f", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-057:v0.1.1"}
{"base_commit": "97e04c464a279500bc740a1151fef5c629796e89", "domain": "monte-carlo-particle-transport", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-cpp-task-058:v0.1.1@sha256:3e1dacc9c447cbaaaa3008662b6f84e7c6cc9bd75dbc0a0d0c48a02bee253599", "environment_image_digest": "sha256:3e1dacc9c447cbaaaa3008662b6f84e7c6cc9bd75dbc0a0d0c48a02bee253599", "environment_image_id": "sha256:3e1dacc9c447cbaaaa3008662b6f84e7c6cc9bd75dbc0a0d0c48a02bee253599", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-cpp-task-058:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python-cpp", "license_gate": "none", "license_source": "LICENSE", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "63f808683274310c304ccc8bb920db3ee776a277b8d33cbe4d8346b79d9c3750", "public_payload_sha256": "6275e3cdda6cf031521c78d6bf577c57d16f546f9bbd4565f39a3f576ef238d0", "release_id": "058", "repository_url": "https://github.com/openmc-dev/openmc", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_058", "title": "Repair a valid OpenMC fixed-source workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cpp-task-058:v0.1.1@sha256:66508091435ada9bb6766098d309d1a932d610da54a2205db48521b3dc8a4e0d", "verifier_image_digest": "sha256:66508091435ada9bb6766098d309d1a932d610da54a2205db48521b3dc8a4e0d", "verifier_image_id": "sha256:66508091435ada9bb6766098d309d1a932d610da54a2205db48521b3dc8a4e0d", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cpp-task-058:v0.1.1"}
{"base_commit": "e4e3ab682f0ff13460877624ecf068b9652ae071", "domain": "microscopy-image-analysis", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-059:v0.1.0@sha256:dec04a1b4fb9014d3f4f70f06966546d3d6055b56a3f1d4ffb8066152d8cff44", "environment_image_digest": "sha256:dec04a1b4fb9014d3f4f70f06966546d3d6055b56a3f1d4ffb8066152d8cff44", "environment_image_id": "sha256:dec04a1b4fb9014d3f4f70f06966546d3d6055b56a3f1d4ffb8066152d8cff44", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-059:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "BSD-3-Clause; CC0-1.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "cc394101fff7d1e6c6c980147684d516a11e61e2a446c0f621450d5b953bf70c", "public_payload_sha256": "488ef0518404cb6129de980bed6c386ce0fced73c65180c29d1fa1dfc624a851", "release_id": "059", "repository_url": "https://github.com/scikit-image/scikit-image", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_059", "title": "Restore physical consistency in calibrated cell morphometry", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-059:v0.1.0@sha256:2dda66b63502d81c2e09a7b0311ca76b3796dc1cd28349f9ece060a35795c8b0", "verifier_image_digest": "sha256:2dda66b63502d81c2e09a7b0311ca76b3796dc1cd28349f9ece060a35795c8b0", "verifier_image_id": "sha256:2dda66b63502d81c2e09a7b0311ca76b3796dc1cd28349f9ece060a35795c8b0", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-059:v0.1.0"}
{"base_commit": "3fd3d97164c6e85c2897ce8b13ba6aace81c2811", "domain": "high-density-extracellular-electrophysiology", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-060:v0.1.0@sha256:61af28db733eec1188ad8b90a4a78404e88b7bfb17cf99800b543292c9545747", "environment_image_digest": "sha256:61af28db733eec1188ad8b90a4a78404e88b7bfb17cf99800b543292c9545747", "environment_image_id": "sha256:61af28db733eec1188ad8b90a4a78404e88b7bfb17cf99800b543292c9545747", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-060:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "CC-BY-4.0; MIT; ODbL-1.0; CC-BY-SA-4.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "f71ff1878d6879fafa4a6be41fb3b83e3db64aa190eb683adbe514ef2af1f8f1", "public_payload_sha256": "80316385eb8e13dbcde03eb53c69e7934a249b600e0dfbcec6286ec48c5dd57f", "release_id": "060", "repository_url": "https://github.com/SpikeInterface/spikeinterface", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_060", "title": "Restore a complete cross-band drift-correction recording", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-060:v0.1.0@sha256:d1a95a1456b922044d1cfa9156bf33ba40628a3115b2ff25b4d6b149dfd1f4bf", "verifier_image_digest": "sha256:d1a95a1456b922044d1cfa9156bf33ba40628a3115b2ff25b4d6b149dfd1f4bf", "verifier_image_id": "sha256:d1a95a1456b922044d1cfa9156bf33ba40628a3115b2ff25b4d6b149dfd1f4bf", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-060:v0.1.0"}
{"base_commit": "62a0d3f037024d4dcf67857fb83d392f2e099ec0", "domain": "astronomical-image-processing", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-c-task-061:v0.1.1@sha256:1ead1c5cac4ffdaf82af9ff33501a577cbed8df429b0004d01932353e35e25b8", "environment_image_digest": "sha256:1ead1c5cac4ffdaf82af9ff33501a577cbed8df429b0004d01932353e35e25b8", "environment_image_id": "sha256:1ead1c5cac4ffdaf82af9ff33501a577cbed8df429b0004d01932353e35e25b8", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-c-task-061:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python-c", "license_gate": "none", "license_source": "LICENSE", "material_license": "BSD-3-Clause; CC-BY-3.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "e018ba172e4f36e9ac6c2ba08a68c48265bf8ba6769a0d1e41ae1fd66097a064", "public_payload_sha256": "aa60b02d450e7fc23118652e520c2fab555aef639668366857d370813dd6a633", "release_id": "061", "repository_url": "https://github.com/astropy/reproject", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_061", "title": "Repair inconsistent celestial image representation in a mosaic", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-c-task-061:v0.1.1@sha256:e9b9718e2ae8dd4a138053ebd99716be920d0268f2e4b7c034b85bb51e80851c", "verifier_image_digest": "sha256:e9b9718e2ae8dd4a138053ebd99716be920d0268f2e4b7c034b85bb51e80851c", "verifier_image_id": "sha256:e9b9718e2ae8dd4a138053ebd99716be920d0268f2e4b7c034b85bb51e80851c", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-c-task-061:v0.1.1"}
{"base_commit": "95b15d576f47923e1f200c0894915a8f46675291", "domain": "computational-materials-science", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-062:v0.1.1@sha256:e88e0630590dc6482901f7fadea3c4770ae6f9ea1115ef33db9b718a6b090574", "environment_image_digest": "sha256:e88e0630590dc6482901f7fadea3c4770ae6f9ea1115ef33db9b718a6b090574", "environment_image_id": "sha256:e88e0630590dc6482901f7fadea3c4770ae6f9ea1115ef33db9b718a6b090574", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-062:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "BSD-3-Clause; CC-BY-4.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "872ec653be2ee37949c79638d5c86792131366a68ae43e2e77adbb1b729933d1", "public_payload_sha256": "37b46ae203774a85fce227f96263194db8267dd69b67449fb58fa62a6b4cbd61", "release_id": "062", "repository_url": "https://github.com/materialsproject/atomate2", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_062", "title": "Repair an inconsistent archived elasticity workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-062:v0.1.1@sha256:ac14a3bfe33e6c172748db20cb6a552eaafced87dccfcc6a808ab4de598b444e", "verifier_image_digest": "sha256:ac14a3bfe33e6c172748db20cb6a552eaafced87dccfcc6a808ab4de598b444e", "verifier_image_id": "sha256:ac14a3bfe33e6c172748db20cb6a552eaafced87dccfcc6a808ab4de598b444e", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-062:v0.1.1"}
{"base_commit": "", "domain": "population-genetics-tree-sequence-statistics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-c-python-task-063:v0.1.1@sha256:1f09e3a4c986be189a1c35ec84f0fd0eed673e498264ed2883d5984043c2e113", "environment_image_digest": "sha256:1f09e3a4c986be189a1c35ec84f0fd0eed673e498264ed2883d5984043c2e113", "environment_image_id": "sha256:1f09e3a4c986be189a1c35ec84f0fd0eed673e498264ed2883d5984043c2e113", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-c-python-task-063:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "c-python", "license_gate": "none", "license_source": "LICENSE", "material_license": "CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "9f3ccc9dceb3e2e4b65a40c04cc07a41c2c5ff6e63257650b1e29d8545839a34", "public_payload_sha256": "11f85264ddf7364c99635fd16088b71210f583c264ab8595fddd62227b40a0a0", "release_id": "063", "repository_url": "https://github.com/tskit-dev/tskit", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_063", "title": "Repair inconsistent population-history estimates after archive curation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-c-python-task-063:v0.1.1@sha256:708641d17e5aa0d5ae7bb62948e3c802e2f63e1f5fdc8b6f41c4a90506ab0ee5", "verifier_image_digest": "sha256:708641d17e5aa0d5ae7bb62948e3c802e2f63e1f5fdc8b6f41c4a90506ab0ee5", "verifier_image_id": "sha256:708641d17e5aa0d5ae7bb62948e3c802e2f63e1f5fdc8b6f41c4a90506ab0ee5", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-c-python-task-063:v0.1.1"}
{"base_commit": "593f0d67cf6a76f4a047f9a4856125c05947cff4", "domain": "computational-chemistry-scientific-data-parsing", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-064:v0.1.1@sha256:b91615199e355f90fbcbbc284128ae5974562118b15e278c0591cfeb00a6fe04", "environment_image_digest": "sha256:b91615199e355f90fbcbbc284128ae5974562118b15e278c0591cfeb00a6fe04", "environment_image_id": "sha256:b91615199e355f90fbcbbc284128ae5974562118b15e278c0591cfeb00a6fe04", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-064:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "BSD-3-Clause; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "daea5f2bac0fdf97fb8aef1d547f768a2d742697d52ef7256878639629bb1b72", "public_payload_sha256": "931cfcfcca1e193baba9d9a904ba1c2ea826fb47565ed18764390870c7f2b6b8", "release_id": "064", "repository_url": "https://github.com/cclib/cclib", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_064", "title": "Repair inconsistent molecular-energy interpretation in a quantum-chemistry log parser", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-064:v0.1.1@sha256:14bfe60853ddf4711f785030658cf749b9b24944845f1c2acb2027711220b4e8", "verifier_image_digest": "sha256:14bfe60853ddf4711f785030658cf749b9b24944845f1c2acb2027711220b4e8", "verifier_image_id": "sha256:14bfe60853ddf4711f785030658cf749b9b24944845f1c2acb2027711220b4e8", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-064:v0.1.1"}
{"base_commit": "c86781b8cbdeea8002c7846d37dc1250045146e6", "domain": "astrophysical hydrodynamics and particle-based field visualization", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-065:v0.1.1@sha256:ab1d33fc7e90eea9245a2f8174dc64bd71b5772fdb1addab0fdf7cf87c15c826", "environment_image_digest": "sha256:ab1d33fc7e90eea9245a2f8174dc64bd71b5772fdb1addab0fdf7cf87c15c826", "environment_image_id": "sha256:ab1d33fc7e90eea9245a2f8174dc64bd71b5772fdb1addab0fdf7cf87c15c826", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-065:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "COPYING.txt", "material_license": "BSD-3-Clause", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "743c5204f6f26d5b4a3eddd58e53b2373d0a50ec0fdb4c13e611c06a4b25c6d1", "public_payload_sha256": "73ff2fb54184a476d2c9a52fab7e72e01ae70582a6d2cc90bec61b68071c2413", "release_id": "065", "repository_url": "https://github.com/yt-project/yt", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_065", "title": "Repair inconsistent particle-field visualization results", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-065:v0.1.1@sha256:7cf23632e18d6c06f29162b88665e2c0e37f37b8c4d7e2d4f911a1394c24a015", "verifier_image_digest": "sha256:7cf23632e18d6c06f29162b88665e2c0e37f37b8c4d7e2d4f911a1394c24a015", "verifier_image_id": "sha256:7cf23632e18d6c06f29162b88665e2c0e37f37b8c4d7e2d4f911a1394c24a015", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-065:v0.1.1"}
{"base_commit": "0b569cdfad5e67f4aec3562bb26460020c7c7354", "domain": "earth-science-data-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-066:v0.1.1@sha256:3769055f64cea8d194ebe727cd68ca764d8709ba324860f095d0f6808ec40545", "environment_image_digest": "sha256:3769055f64cea8d194ebe727cd68ca764d8709ba324860f095d0f6808ec40545", "environment_image_id": "sha256:3769055f64cea8d194ebe727cd68ca764d8709ba324860f095d0f6808ec40545", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-066:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "COPYING", "material_license": "LGPL-3.0-or-later", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "bba8dad05d78e0be623c0a69d7b96b985835a0a9e0fe5a911ca31e925798a6b8", "public_payload_sha256": "c3f82c807772ab9a6a3fd61b0cc593173eadb82aa1d6eae635d722f76563dac5", "release_id": "066", "repository_url": "https://github.com/SciTools/iris", "restricted_license": true, "restricted_reason": "The Iris source snapshot is LGPL-3.0-or-later; explicit restricted-license opt-in is required for this task.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-or-later", "status": "dockerhub-published", "task_path": "tasks/task_066", "title": "Restore regional climate-model validation consistency", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-066:v0.1.1@sha256:99bf32820ff34946dd60557e985cd827ec30ade8e3c5f8fe675246f86aec512f", "verifier_image_digest": "sha256:99bf32820ff34946dd60557e985cd827ec30ade8e3c5f8fe675246f86aec512f", "verifier_image_id": "sha256:99bf32820ff34946dd60557e985cd827ec30ade8e3c5f8fe675246f86aec512f", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-066:v0.1.1"}
{"base_commit": "d1e654cf59a5d5761f5586bca1102a1590ae6e32", "domain": "climate-fire-weather", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-067:v0.1.1@sha256:766e978fb083474965494e7d8010cad9f2eb9b85178a991db82a46c626825dcb", "environment_image_digest": "sha256:766e978fb083474965494e7d8010cad9f2eb9b85178a991db82a46c626825dcb", "environment_image_id": "sha256:766e978fb083474965494e7d8010cad9f2eb9b85178a991db82a46c626825dcb", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-067:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "Apache-2.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "ab73bddee4e1a9cf953c5ffc9261de0b8a4bddbbe926d43a279dedf142bed459", "public_payload_sha256": "59d12e07a39bf7e5c8e3d1a3f966cac3a12eca55499b9b45a07ba77585a7486c", "release_id": "067", "repository_url": "https://github.com/Ouranosinc/xclim", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_067", "title": "Repair a seasonal fire-weather state transition", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-067:v0.1.1@sha256:c89861f5ff214b94dfb9407e7c40d85343f1b7a0d07437d96078249abd4c909c", "verifier_image_digest": "sha256:c89861f5ff214b94dfb9407e7c40d85343f1b7a0d07437d96078249abd4c909c", "verifier_image_id": "sha256:c89861f5ff214b94dfb9407e7c40d85343f1b7a0d07437d96078249abd4c909c", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-067:v0.1.1"}
{"base_commit": "a4dde3f93c75dff09e9a1ddaf0db2e54c91ac5e3", "domain": "genomic-variant-data-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-068:v0.1.1@sha256:efcb7d617872dddded3c169401e810de68d9b3a82d57ee11e982aeb624431b57", "environment_image_digest": "sha256:efcb7d617872dddded3c169401e810de68d9b3a82d57ee11e982aeb624431b57", "environment_image_id": "sha256:efcb7d617872dddded3c169401e810de68d9b3a82d57ee11e982aeb624431b57", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-068:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "c", "license_gate": "none", "license_source": "LICENSE", "material_license": "BSD-3-Clause", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "70f186110a677cb2d9d634c87c1af38442d29c4ad6fbd6594fe023b35cbd5bf5", "public_payload_sha256": "888a97209250e1a9cd032def6487c0e89dfeb70681e476332331a99536361397", "release_id": "068", "repository_url": "https://github.com/samtools/htslib", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_068", "title": "Restore biologically consistent retrieval from a VCF archive", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-068:v0.1.1@sha256:66bb2ef9c1a5827af5909b40d7bee327a354583a3d251dd64aa0ba301f4f4df0", "verifier_image_digest": "sha256:66bb2ef9c1a5827af5909b40d7bee327a354583a3d251dd64aa0ba301f4f4df0", "verifier_image_id": "sha256:66bb2ef9c1a5827af5909b40d7bee327a354583a3d251dd64aa0ba301f4f4df0", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-068:v0.1.1"}
{"base_commit": "ba2be42c714fffb6b62ea13e7ecfbecb5f4a4d9a", "domain": "genomics-contact-map-analysis", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-069:v0.1.1@sha256:adfe5d88e0bf8d979d6689b4742a88c1b17e9fb4e46d52cc2ee6a3178efce7f8", "environment_image_digest": "sha256:adfe5d88e0bf8d979d6689b4742a88c1b17e9fb4e46d52cc2ee6a3178efce7f8", "environment_image_id": "sha256:adfe5d88e0bf8d979d6689b4742a88c1b17e9fb4e46d52cc2ee6a3178efce7f8", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-069:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "6f8bbdc4d2621334ec55e91d66e3ed210a00d179379ce7c32924d08c8b1fec6d", "public_payload_sha256": "5027e57b9549b6302e0a89500be54b77f98ed5b892b62619764b4d0959b34103", "release_id": "069", "repository_url": "https://github.com/open2c/cooltools", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_069", "title": "Restore a complete Hi-C contact-decay analysis", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-069:v0.1.1@sha256:43aebaeb0f53e9b42e2cfe6c5273fa0f7789565873dda6a204d5343eb787ef77", "verifier_image_digest": "sha256:43aebaeb0f53e9b42e2cfe6c5273fa0f7789565873dda6a204d5343eb787ef77", "verifier_image_id": "sha256:43aebaeb0f53e9b42e2cfe6c5273fa0f7789565873dda6a204d5343eb787ef77", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-069:v0.1.1"}
{"base_commit": "f509b761a5231e9f108780c88c2b3781266e7b90", "domain": "proteomics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-070:v0.1.1@sha256:9062d901d1d5cf0b21e40c6f2ef1e8a74f031688a155c2494ea634917542f4b9", "environment_image_digest": "sha256:9062d901d1d5cf0b21e40c6f2ef1e8a74f031688a155c2494ea634917542f4b9", "environment_image_id": "sha256:9062d901d1d5cf0b21e40c6f2ef1e8a74f031688a155c2494ea634917542f4b9", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-070:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "Apache-2.0; CC-BY-ND-4.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "1a6dd13ea29f70098b84055742b13cefa7b6b27968057e655a3f50832b3dfed4", "public_payload_sha256": "dd10099299550a104358e0e689672b03775c4f450005954da2bcef0043499615", "release_id": "070", "repository_url": "https://github.com/levitsky/pyteomics", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_070", "title": "Restore chemically consistent proteoform ion annotations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-070:v0.1.1@sha256:be0a2af61ac002f61b716c27295185aaa240e5e2c0a1f59d3883a9e0455ce565", "verifier_image_digest": "sha256:be0a2af61ac002f61b716c27295185aaa240e5e2c0a1f59d3883a9e0455ce565", "verifier_image_id": "sha256:be0a2af61ac002f61b716c27295185aaa240e5e2c0a1f59d3883a9e0455ce565", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-070:v0.1.1"}
{"base_commit": "3a7adedc45c9a94585ec19bbd4622ac9f483ab9c", "domain": "grazing-incidence-and-fiber-x-ray-scattering", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-071:v0.1.0@sha256:08968262336c765e8d683cc867e2e0c3db50a99cee923ea8fa000bf4523a843d", "environment_image_digest": "sha256:08968262336c765e8d683cc867e2e0c3db50a99cee923ea8fa000bf4523a843d", "environment_image_id": "sha256:08968262336c765e8d683cc867e2e0c3db50a99cee923ea8fa000bf4523a843d", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-071:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:copyright@3a7adedc45c9a94585ec19bbd4622ac9f483ab9c", "material_license": "MIT/X11 (BSD-like; see upstream copyright manifest)", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "659f258616ed5e6514aca604e947b5c2f59ee998ada2a42502c4166b23b93e05", "public_payload_sha256": "2905839a4d61cd13eb482bff4f3d42e776de6828792e8149091775af18e1900e", "release_id": "071", "repository_url": "https://github.com/silx-kit/pyFAI", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT/X11 (BSD-like; see upstream copyright manifest)", "status": "dockerhub-published", "task_path": "tasks/task_071", "title": "Repair an orientation-sensitive fiber-scattering reduction", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-071:v0.1.0@sha256:0039c955ffd15cd0020334c375dd24e6c41c1b1b2a6b59b392c647db32c47882", "verifier_image_digest": "sha256:0039c955ffd15cd0020334c375dd24e6c41c1b1b2a6b59b392c647db32c47882", "verifier_image_id": "sha256:0039c955ffd15cd0020334c375dd24e6c41c1b1b2a6b59b392c647db32c47882", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-071:v0.1.0"}
{"base_commit": "b69de21c8610853493bc81d3eac79644554e4bda", "domain": "medical-imaging-color-pixel-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-072:v0.1.0@sha256:c9746b594a561e16a92a0718356d2bde20f564a61d882bbce1af3bcd1658dad3", "environment_image_digest": "sha256:c9746b594a561e16a92a0718356d2bde20f564a61d882bbce1af3bcd1658dad3", "environment_image_id": "sha256:c9746b594a561e16a92a0718356d2bde20f564a61d882bbce1af3bcd1658dad3", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-072:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "5e3eec9815dad551219073128d86675a463fd7ee9020c78350a4dc5de407e8ef", "public_payload_sha256": "8d4349b082362535dfc9d35cf9fa1a79f4175e82a2900e0a33e0f23a92b98e65", "release_id": "072", "repository_url": "https://github.com/pydicom/pydicom", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_072", "title": "Repair an incomplete DICOM color image presentation workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-072:v0.1.0@sha256:8683aa3c574011f36df457c54a443457cd37078c2ca48f85fcb46015c431b31d", "verifier_image_digest": "sha256:8683aa3c574011f36df457c54a443457cd37078c2ca48f85fcb46015c431b31d", "verifier_image_id": "sha256:8683aa3c574011f36df457c54a443457cd37078c2ca48f85fcb46015c431b31d", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-072:v0.1.0"}
{"base_commit": "f8c3b8aa5473e078f91c86dcee7340eb9ed3eb97", "domain": "structural-biology-pdbx-macromolecular-connectivity", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-073:v0.1.0@sha256:fca7d2514acb9214baf529a5d4bfddbe5e165ba24cbea63cb4d380f5f5bea483", "environment_image_digest": "sha256:fca7d2514acb9214baf529a5d4bfddbe5e165ba24cbea63cb4d380f5f5bea483", "environment_image_id": "sha256:fca7d2514acb9214baf529a5d4bfddbe5e165ba24cbea63cb4d380f5f5bea483", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-073:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.rst", "material_license": "BSD-3-Clause; CC0-1.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "29984f1b6384b6aabb1dea6e5a38869a4a494e6f4c482a05838036b74c57e7f2", "public_payload_sha256": "a35b8e2a51e00a9c1758afd9349401a9da1a12e081311d0999fd8b57a8a3c466", "release_id": "073", "repository_url": "https://github.com/biotite-dev/biotite", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_073", "title": "Repair inconsistent alternate-conformer structure connectivity", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-073:v0.1.0@sha256:6041a2f1f781e1e02e908984c07c6de7a1e2edd67a3ce90529522ebc2e72aee8", "verifier_image_digest": "sha256:6041a2f1f781e1e02e908984c07c6de7a1e2edd67a3ce90529522ebc2e72aee8", "verifier_image_id": "sha256:6041a2f1f781e1e02e908984c07c6de7a1e2edd67a3ce90529522ebc2e72aee8", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-073:v0.1.0"}
{"base_commit": "e365079ea71190aaa0dc96d22253d3888c47abf9", "domain": "electronic-structure-nonorthogonal-eigenproblems", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-074:v0.1.0@sha256:717c4de698523729922644dc8f42dbf98071dbe48c25cf1016d425d2ceb0e49f", "environment_image_digest": "sha256:717c4de698523729922644dc8f42dbf98071dbe48c25cf1016d425d2ceb0e49f", "environment_image_id": "sha256:717c4de698523729922644dc8f42dbf98071dbe48c25cf1016d425d2ceb0e49f", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-074:v0.1.0", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "material_license": "LGPL-3.0-family", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "adffb57a85b49134fd1804378407356148a377925ff011d805d3a5e34b906c8c", "public_payload_sha256": "2383d14efcf296069395c4704ae80ca3ac084da33ac9c9f87e1e08a4693c2a98", "release_id": "074", "repository_url": "https://github.com/deepmodeling/DeePTB", "restricted_license": true, "restricted_reason": "The DeePTB source snapshot is LGPL-3.0-family; explicit restricted-license opt-in is required. The cited article is CC BY-NC-ND and is not bundled.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_074", "title": "Repair an ill-conditioned overlap band-postprocessing workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-074:v0.1.0@sha256:874067a5199b4db19f575c074b7cd51c1eddf03f7aa13c97810ea2873c917d86", "verifier_image_digest": "sha256:874067a5199b4db19f575c074b7cd51c1eddf03f7aa13c97810ea2873c917d86", "verifier_image_id": "sha256:874067a5199b4db19f575c074b7cd51c1eddf03f7aa13c97810ea2873c917d86", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-074:v0.1.0"}
{"base_commit": "a9bcbc505de7d905dbc2a598b10c17a49e0131d8", "domain": "molecular-dynamics-machine-learning-potentials", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-075:v0.1.0@sha256:7beaf3765d9cf49e2d3f647833f63266dfa15bc9978b753755050a66a7ec15dc", "environment_image_digest": "sha256:7beaf3765d9cf49e2d3f647833f63266dfa15bc9978b753755050a66a7ec15dc", "environment_image_id": "sha256:7beaf3765d9cf49e2d3f647833f63266dfa15bc9978b753755050a66a7ec15dc", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-c-task-075:v0.1.0", "gpl_family": true, "image_platform": "linux/amd64", "language": "c++", "license_gate": "gpl-family", "license_source": "LICENSE", "material_license": "LGPL-3.0-family", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "9621945cc7f599ea75931db429c641bb6a8db2ab3020497db5a1f2a9187101f7", "public_payload_sha256": "bafffe305071135e9e917ef331a734a2f6500acf5b2bf8ed26df67f92de15566", "release_id": "075", "repository_url": "https://github.com/deepmodeling/deepmd-kit", "restricted_license": true, "restricted_reason": "The DeePMD-kit source snapshot is LGPL-3.0-family; explicit restricted-license opt-in is required for this task.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_075", "title": "Restore consistent compressed Deep Potential tabulation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-075:v0.1.0@sha256:c50d05f06eee0035eb02e057017cbdbfae6a9855a900ac819bb90b937285a022", "verifier_image_digest": "sha256:c50d05f06eee0035eb02e057017cbdbfae6a9855a900ac819bb90b937285a022", "verifier_image_id": "sha256:c50d05f06eee0035eb02e057017cbdbfae6a9855a900ac819bb90b937285a022", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-c-task-075:v0.1.0"}
{"base_commit": "5f57b6408864caab207c28f773a14c6261689abe", "domain": "convex-optimization-parametric-workflows", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-076:v0.1.0@sha256:1a50e20a9caf81566ac7f3f9d356b04b8352a7eb3532f8a5543307ef3f0670fe", "environment_image_digest": "sha256:1a50e20a9caf81566ac7f3f9d356b04b8352a7eb3532f8a5543307ef3f0670fe", "environment_image_id": "sha256:1a50e20a9caf81566ac7f3f9d356b04b8352a7eb3532f8a5543307ef3f0670fe", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-076:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "c2303ccea73430e7cca4a82672bdf8c5ea7465237e18f465358267c979f4cb4d", "release_id": "076", "repository_url": "https://github.com/cvxpy/cvxpy", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_076", "title": "Repair a batched parametric tracking workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-076:v0.1.0@sha256:c40da6ce2cafe0194e2d74ca0380587b696890713c163a17624a855c86247404", "verifier_image_digest": "sha256:c40da6ce2cafe0194e2d74ca0380587b696890713c163a17624a855c86247404", "verifier_image_id": "sha256:c40da6ce2cafe0194e2d74ca0380587b696890713c163a17624a855c86247404", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-076:v0.1.0"}
{"base_commit": "d2872f6c4d7c99b16f8a71d99cd56d0a5fe54695", "domain": "computational-geometry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-077:v0.1.1@sha256:beb11a067f8267b19c73e9994ab2f4c364bdcca5e7c94e58b1454fe75f4f6c95", "environment_image_digest": "sha256:beb11a067f8267b19c73e9994ab2f4c364bdcca5e7c94e58b1454fe75f4f6c95", "environment_image_id": "sha256:beb11a067f8267b19c73e9994ab2f4c364bdcca5e7c94e58b1454fe75f4f6c95", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-077:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "281a98b13117b5df40f97a7237a835fd669856b82c6afb0913e700dc35f33055", "release_id": "077", "repository_url": "https://github.com/shapely/shapely", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_077", "title": "Repair an inconsistent oriented-envelope fallback workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-077:v0.1.1@sha256:eb936b5b0a6db0add7ea609d3b1e2fa52c2fe210e8cc32e301b66ce3221d9051", "verifier_image_digest": "sha256:eb936b5b0a6db0add7ea609d3b1e2fa52c2fe210e8cc32e301b66ce3221d9051", "verifier_image_id": "sha256:eb936b5b0a6db0add7ea609d3b1e2fa52c2fe210e8cc32e301b66ce3221d9051", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-077:v0.1.1"}
{"base_commit": "eda83f4a57000d5f6763ee7afa9afacebbe0fd68", "domain": "astronomical-image-analysis-and-wcs-aperture-photometry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-078:v0.1.1@sha256:0e1849bbff6fe2eb30b54b2eaf296f590390fba11f7aeea4afc3dbdad2b1e336", "environment_image_digest": "sha256:0e1849bbff6fe2eb30b54b2eaf296f590390fba11f7aeea4afc3dbdad2b1e336", "environment_image_id": "sha256:0e1849bbff6fe2eb30b54b2eaf296f590390fba11f7aeea4afc3dbdad2b1e336", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-078:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.rst", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "e60c70e110ceae698185704aded868fcebb304d67ce96dc699c2a52d8640e254", "release_id": "078", "repository_url": "https://github.com/astropy/photutils", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_078", "title": "Repair an inconsistent astronomical aperture workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-078:v0.1.1@sha256:ca6a16eab260d44233b515576ba7b879285e92680a316d2fda4559260e18d933", "verifier_image_digest": "sha256:ca6a16eab260d44233b515576ba7b879285e92680a316d2fda4559260e18d933", "verifier_image_id": "sha256:ca6a16eab260d44233b515576ba7b879285e92680a316d2fda4559260e18d933", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-078:v0.1.1"}
{"base_commit": "55f4e3437b6fb68deafa533cb00277b119e6eb8a", "domain": "computational-chemistry-molecular-representations", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-079:v0.1.1@sha256:4af19fec4854df53db9bf131d3d49bef7f35b61277dadbde83c9033e77a2f881", "environment_image_digest": "sha256:4af19fec4854df53db9bf131d3d49bef7f35b61277dadbde83c9033e77a2f881", "environment_image_id": "sha256:4af19fec4854df53db9bf131d3d49bef7f35b61277dadbde83c9033e77a2f881", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-079:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "4eb5b892be7fa0164e7a792f8131d6797e5eaecf3a15b1d6fbd1c41aad61fe2c", "release_id": "079", "repository_url": "https://github.com/aspuru-guzik-group/selfies", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_079", "title": "Repair molecular-string translation for catalogue workflows", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-079:v0.1.1@sha256:6c796c01b6520dfa6df8664a98ca6f5686032c03d6a7cba8f45f697da9aa7206", "verifier_image_digest": "sha256:6c796c01b6520dfa6df8664a98ca6f5686032c03d6a7cba8f45f697da9aa7206", "verifier_image_id": "sha256:6c796c01b6520dfa6df8664a98ca6f5686032c03d6a7cba8f45f697da9aa7206", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-079:v0.1.1"}
{"base_commit": "7d252520dbf81b168a2789a6aedfb75d04a21061", "domain": "geospatial-raster-reprojection", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-080:v0.1.0@sha256:bd33e55e04ded03f1911abe6f673e4217c4fed04e14db72be630c1503cd10735", "environment_image_digest": "sha256:bd33e55e04ded03f1911abe6f673e4217c4fed04e14db72be630c1503cd10735", "environment_image_id": "sha256:bd33e55e04ded03f1911abe6f673e4217c4fed04e14db72be630c1503cd10735", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-080:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "public_payload_sha256": "2e7d63a1052c7b94245de245deed7e14e20169bb0ad2447c854e4f1d6026fa6e", "release_id": "080", "repository_url": "https://github.com/xarray-contrib/xarray-spatial", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_080", "title": "Repair inconsistent geospatial raster remapping", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-080:v0.1.0@sha256:0bd2b80b544ce97b0ecbab0c397a5d68014ee7cb2c3133be648db3d3ca0045ed", "verifier_image_digest": "sha256:0bd2b80b544ce97b0ecbab0c397a5d68014ee7cb2c3133be648db3d3ca0045ed", "verifier_image_id": "sha256:0bd2b80b544ce97b0ecbab0c397a5d68014ee7cb2c3133be648db3d3ca0045ed", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-080:v0.1.0"}
{"base_commit": "9acb412357f025982b5817bda18bcb5d057a05ba", "domain": "single-cell-annotated-data-containers", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-081:v0.1.1@sha256:452ada5f59b6d0df7986e34626d0b77a8baa81eaab14523e8bb1a56ebf54eef8", "environment_image_digest": "sha256:452ada5f59b6d0df7986e34626d0b77a8baa81eaab14523e8bb1a56ebf54eef8", "environment_image_id": "sha256:452ada5f59b6d0df7986e34626d0b77a8baa81eaab14523e8bb1a56ebf54eef8", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-081:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "c4b015e7778c7dc9d33fb8afa94f1336504698cbf1259b0a76a43b843b72928e", "release_id": "081", "repository_url": "https://github.com/scverse/anndata", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_081", "title": "Repair local study workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-081:v0.1.1@sha256:3673333288212329c2cc68a409ecd68b9070134b95cb2e2e202c123949d66a39", "verifier_image_digest": "sha256:3673333288212329c2cc68a409ecd68b9070134b95cb2e2e202c123949d66a39", "verifier_image_id": "sha256:3673333288212329c2cc68a409ecd68b9070134b95cb2e2e202c123949d66a39", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-081:v0.1.1"}
{"base_commit": "02a442c6bd7da9b5b2c9f958d3a103f5d6cd2a27", "domain": "atomistic-machine-learning-and-molecular-simulation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-082:v0.1.1@sha256:117809d14e4a0e2a65fbcb0e56b412d3314ee86fba7a566265964105614a37b4", "environment_image_digest": "sha256:117809d14e4a0e2a65fbcb0e56b412d3314ee86fba7a566265964105614a37b4", "environment_image_id": "sha256:117809d14e4a0e2a65fbcb0e56b412d3314ee86fba7a566265964105614a37b4", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-082:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "450071a5b7f7e1693dac697a1f19332287a3022c644dc1043ae394bfd96f31fa", "release_id": "082", "repository_url": "https://github.com/deepmodeling/dpgen", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_082", "title": "Repair a workflow consistency bug", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-082:v0.1.1@sha256:44182cef33ab2fc2d8d48a03e265e4e0b02fa9d058c50442e2d1664415e056ba", "verifier_image_digest": "sha256:44182cef33ab2fc2d8d48a03e265e4e0b02fa9d058c50442e2d1664415e056ba", "verifier_image_id": "sha256:44182cef33ab2fc2d8d48a03e265e4e0b02fa9d058c50442e2d1664415e056ba", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-082:v0.1.1"}
{"base_commit": "37b0bef6fd9d5945f1b752ac82d4f8564728cd8b", "domain": "computational-chemistry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-083:v0.1.1@sha256:67c242e115420f16eb9e9bab09c8c7feeac2ed61f71ce493f4133ff9cff9ed3c", "environment_image_digest": "sha256:67c242e115420f16eb9e9bab09c8c7feeac2ed61f71ce493f4133ff9cff9ed3c", "environment_image_id": "sha256:67c242e115420f16eb9e9bab09c8c7feeac2ed61f71ce493f4133ff9cff9ed3c", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-083:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "48f2557e6046a003e567fb8b9055d9a6f9a93401f664313f9c04cedadd30780c", "release_id": "083", "repository_url": "https://github.com/deepmodeling/reacnetgenerator", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_083", "title": "Repair bond-order species reporting", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-083:v0.1.1@sha256:805c263e506a34e81845de31330a863db80376580715a08d4b4c23f9354d911e", "verifier_image_digest": "sha256:805c263e506a34e81845de31330a863db80376580715a08d4b4c23f9354d911e", "verifier_image_id": "sha256:805c263e506a34e81845de31330a863db80376580715a08d4b4c23f9354d911e", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-083:v0.1.1"}
{"base_commit": "80abfc5037876c0e883dcb58cd96521397e3fe36", "domain": "materials-science-scientific-data-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-084:v0.1.1@sha256:f711ef601b2c039c5d1593175d549cce987bcfcbfc057356507d25b14d1141a2", "environment_image_digest": "sha256:f711ef601b2c039c5d1593175d549cce987bcfcbfc057356507d25b14d1141a2", "environment_image_id": "sha256:f711ef601b2c039c5d1593175d549cce987bcfcbfc057356507d25b14d1141a2", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-084:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "LICENSE", "material_licenses": ["LGPL-3.0-or-later"], "materials_provenance": "fixtures/PROVENANCE.md", "public_payload_sha256": "10df205f59e7cf7c7e6422df207e68ea5ba17619105bc2b77a5ace7cf1e5460c", "release_id": "084", "repository_url": "https://github.com/deepmodeling/dpdata", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_084", "title": "Repair ABACUS relaxation archive/reload semantics", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-084:v0.1.1@sha256:e22e29a19f68d6cca283927bb26da82063156e070f86f32df8b06bfac15aa3f9", "verifier_image_digest": "sha256:e22e29a19f68d6cca283927bb26da82063156e070f86f32df8b06bfac15aa3f9", "verifier_image_id": "sha256:e22e29a19f68d6cca283927bb26da82063156e070f86f32df8b06bfac15aa3f9", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-084:v0.1.1"}
{"base_commit": "d4da8c5027b643291f3a6295efd4340ce79d6a36", "domain": "computational-chemistry-and-solvation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-fortran-task-085:v0.1.1@sha256:fc28d7af99fa395f69d2e98d62fe2b3cf22befcd2c824e9aa769eaf3ac1e60d2", "environment_image_digest": "sha256:fc28d7af99fa395f69d2e98d62fe2b3cf22befcd2c824e9aa769eaf3ac1e60d2", "environment_image_id": "sha256:fc28d7af99fa395f69d2e98d62fe2b3cf22befcd2c824e9aa769eaf3ac1e60d2", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-fortran-task-085:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "fortran", "license_gate": "gpl-family", "license_source": "LICENSE", "material_licenses": ["CC-BY-SA-4.0"], "materials_provenance": "fixtures/PROVENANCE.md", "public_payload_sha256": "a946e0e51876186f7373b258d91aeffc972f3af15412bbbecc2c18872b576ff2", "release_id": "085", "repository_url": "https://github.com/dftbplus/dftbplus", "restricted_license": true, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "LGPL-3.0-family", "status": "dockerhub-published", "task_path": "tasks/task_085", "title": "Inconsistent archived observables", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-fortran-task-085:v0.1.1@sha256:57de442f9e3510938ba8203803884f9c824a7d1f1eeee571783fdfa1431dbf56", "verifier_image_digest": "sha256:57de442f9e3510938ba8203803884f9c824a7d1f1eeee571783fdfa1431dbf56", "verifier_image_id": "sha256:57de442f9e3510938ba8203803884f9c824a7d1f1eeee571783fdfa1431dbf56", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-fortran-task-085:v0.1.1"}
{"base_commit": "02b415ba8bb25244bc5e3ad970491f0fbbea0292", "domain": "atomistic-machine-learning-potentials", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-086:v0.1.0@sha256:7a54bd7e811a51abdd7571abbc03213eece0310016b174bfa52dcbe4ad171476", "environment_image_digest": "sha256:7a54bd7e811a51abdd7571abbc03213eece0310016b174bfa52dcbe4ad171476", "environment_image_id": "sha256:7a54bd7e811a51abdd7571abbc03213eece0310016b174bfa52dcbe4ad171476", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-086:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "dd83643eed59e22c0cf5fa9d29e4de990944b8add3edd5058391df75a585f537", "release_id": "086", "repository_url": "https://github.com/materialyzeai/matgl", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_086", "title": "Repair a silent MatGL fine-tuning incompatibility", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-086:v0.1.0@sha256:fb47312ac7443db59115807334c5d2345e3a2fb7a8f83d89bc8bfb48f7ce4bac", "verifier_image_digest": "sha256:fb47312ac7443db59115807334c5d2345e3a2fb7a8f83d89bc8bfb48f7ce4bac", "verifier_image_id": "sha256:fb47312ac7443db59115807334c5d2345e3a2fb7a8f83d89bc8bfb48f7ce4bac", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-086:v0.1.0"}
{"base_commit": "ee6016ab81dd649ab40439d75212f35669302810", "domain": "diffusion-mri-denoising", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-087:v0.1.0@sha256:5a00e4d7a825618ba70259ef5c5e229f7ba2549ab7648ead6fc91fce31256793", "environment_image_digest": "sha256:5a00e4d7a825618ba70259ef5c5e229f7ba2549ab7648ead6fc91fce31256793", "environment_image_id": "sha256:5a00e4d7a825618ba70259ef5c5e229f7ba2549ab7648ead6fc91fce31256793", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-087:v0.1.0", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "public_payload_sha256": "442792643e44ca3c36c70b3d63c80708e9f58b5972e5bdf43e90834720834814", "release_id": "087", "repository_url": "https://github.com/dipy/dipy", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_087", "title": "Repair a silent diffusion-MRI denoising inconsistency", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-087:v0.1.0@sha256:b1ce39c75913bccef5f09acfd2b989857c071fc64c7fdc0dbff092e14dc5270f", "verifier_image_digest": "sha256:b1ce39c75913bccef5f09acfd2b989857c071fc64c7fdc0dbff092e14dc5270f", "verifier_image_id": "sha256:b1ce39c75913bccef5f09acfd2b989857c071fc64c7fdc0dbff092e14dc5270f", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-087:v0.1.0"}
{"base_commit": "0b071e369a88f6672accc2a99c40d3b4b334f2f9", "domain": "boundary-aggregation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-088:v0.1.1@sha256:f9280d74fccc2dc154eebe06728b65ab7e438fdaacbfe45254563c53ee388e8c", "environment_image_digest": "sha256:f9280d74fccc2dc154eebe06728b65ab7e438fdaacbfe45254563c53ee388e8c", "environment_image_id": "sha256:f9280d74fccc2dc154eebe06728b65ab7e438fdaacbfe45254563c53ee388e8c", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-088:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "5e7474f8aa8269a9d76e03f048cce31b30e91fadfa8bb5e3401d63b59c63ddbf", "release_id": "088", "repository_url": "https://github.com/pydata/xarray", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_088", "title": "Repair a boundary aggregation failure", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-088:v0.1.1@sha256:17b563aa055029b65891898ca6dce79e1bd4821251d6ef7eed607f2702833712", "verifier_image_digest": "sha256:17b563aa055029b65891898ca6dce79e1bd4821251d6ef7eed607f2702833712", "verifier_image_id": "sha256:17b563aa055029b65891898ca6dce79e1bd4821251d6ef7eed607f2702833712", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-088:v0.1.1"}
{"base_commit": "6ba33bdd48bf336a81400147d2870323b241e457", "domain": "computational-chemistry-spectroscopy", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-089:v0.1.1@sha256:32379f2d0e61a69bb030beecefeb55a173d3bd338f4d01399445aa6b4238a155", "environment_image_digest": "sha256:32379f2d0e61a69bb030beecefeb55a173d3bd338f4d01399445aa6b4238a155", "environment_image_id": "sha256:32379f2d0e61a69bb030beecefeb55a173d3bd338f4d01399445aa6b4238a155", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-089:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_licenses": ["MIT"], "materials_provenance": "fixtures/PROVENANCE.md", "public_payload_sha256": "1aa83928a461ec6d8531b1c81d25c21cf4a8497ec1aeb7e84a6da9d7b18dd9f5", "release_id": "089", "repository_url": "https://github.com/cclib/cclib", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_089", "title": "Repair inconsistent ORCA excited-state oscillator strengths", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-089:v0.1.1@sha256:81bdeadb79aef5428d6c184bfe73a9c8612cd35576817b8e3b650bbd25daea9f", "verifier_image_digest": "sha256:81bdeadb79aef5428d6c184bfe73a9c8612cd35576817b8e3b650bbd25daea9f", "verifier_image_id": "sha256:81bdeadb79aef5428d6c184bfe73a9c8612cd35576817b8e3b650bbd25daea9f", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-089:v0.1.1"}
{"base_commit": "a3494234497a4507537c8fc5a89081bdb09b1954", "domain": "nuclear-magnetic-resonance-spectroscopy", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-090:v0.1.1@sha256:dac2e528dc0a2d57797793e4c9d696b73ffed938891a29bb5ecaa0e4dc2386a1", "environment_image_digest": "sha256:dac2e528dc0a2d57797793e4c9d696b73ffed938891a29bb5ecaa0e4dc2386a1", "environment_image_id": "sha256:dac2e528dc0a2d57797793e4c9d696b73ffed938891a29bb5ecaa0e4dc2386a1", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-090:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_licenses": null, "materials_provenance": null, "public_payload_sha256": "ede5e6decc45aef565117030438e7bdd9b8c1b0a663c92381ed7da61bae6a227", "release_id": "090", "repository_url": "https://github.com/jjhelmus/nmrglue", "restricted_license": false, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_090", "title": "Restore multidimensional NMR acquisition grids", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-090:v0.1.1@sha256:3219d6de7809aaa4ea68f82d5f4ac1bceae44d2480a9ae20f47db039661ad8d6", "verifier_image_digest": "sha256:3219d6de7809aaa4ea68f82d5f4ac1bceae44d2480a9ae20f47db039661ad8d6", "verifier_image_id": "sha256:3219d6de7809aaa4ea68f82d5f4ac1bceae44d2480a9ae20f47db039661ad8d6", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-090:v0.1.1"}
{"base_commit": "c8cfee71f3ce5d92c5b5f6ca3d363f8f3a9f4495", "domain": "materials-science-volumetric-data-semantics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-091:v0.1.1@sha256:ca4f4be9a9a075ea6e35a022b447be66e8704dd9ef3568a6c0386ccbeadc2a19", "environment_image_digest": "sha256:ca4f4be9a9a075ea6e35a022b447be66e8704dd9ef3568a6c0386ccbeadc2a19", "environment_image_id": "sha256:ca4f4be9a9a075ea6e35a022b447be66e8704dd9ef3568a6c0386ccbeadc2a19", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-091:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "cabe86733a5ea0ca8b200fc6c1819b593a88d79cf097138474307aa79f763a96", "public_payload_sha256": "4a4914ccaf56efca799866d954fa9a03095f2b866448d2270d5957c89ca3cdbb", "release_id": "091", "repository_url": "https://github.com/materialsproject/pymatgen-core", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_091", "title": "Repair a workflow regression", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-091:v0.1.1@sha256:ec8f7cd03251aa71c0c771816e9833c0daec737c669dc482635be41873933529", "verifier_image_digest": "sha256:ec8f7cd03251aa71c0c771816e9833c0daec737c669dc482635be41873933529", "verifier_image_id": "sha256:ec8f7cd03251aa71c0c771816e9833c0daec737c669dc482635be41873933529", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-091:v0.1.1"}
{"base_commit": "1f367d55d1bac14dd6b9e0cd5746574fcfab9a59", "domain": "ai-chemistry-reaction-property-learning", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-092:v0.1.1@sha256:1fdc4b0cb3aba2319615b013e7563633d0ca4903bfb4c43ce09c0e97f5be33f4", "environment_image_digest": "sha256:1fdc4b0cb3aba2319615b013e7563633d0ca4903bfb4c43ce09c0e97f5be33f4", "environment_image_id": "sha256:1fdc4b0cb3aba2319615b013e7563633d0ca4903bfb4c43ce09c0e97f5be33f4", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-092:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "CC-BY-NC-ND-4.0 and CC-BY-4.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "47f3e82e7dc2461a29eaab35e5e76c6f701c5dc8733dcfed95bd537ee92dd90d", "public_payload_sha256": "c291d415ccd2e70e47144f5f0165dbbf3c715b19888a5cd27277fc3f24f0653b", "release_id": "092", "repository_url": "https://github.com/chemprop/chemprop", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_092", "title": "Repair inconsistent Chemprop reaction observations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-092:v0.1.1@sha256:c2f3487455d2635edf02c1287cdd318c0679ea22f478d6a871150d5a5447f948", "verifier_image_digest": "sha256:c2f3487455d2635edf02c1287cdd318c0679ea22f478d6a871150d5a5447f948", "verifier_image_id": "sha256:c2f3487455d2635edf02c1287cdd318c0679ea22f478d6a871150d5a5447f948", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-092:v0.1.1"}
{"base_commit": "5a644e4edcc37e5c963e52fda6fab4c85b3ff02e", "domain": "medical-image-processing", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-093:v0.1.1@sha256:d25c6fa752227d38fd8fab602f529a3fb79a7a8cc993da5c015c457d901648c6", "environment_image_digest": "sha256:d25c6fa752227d38fd8fab602f529a3fb79a7a8cc993da5c015c457d901648c6", "environment_image_id": "sha256:d25c6fa752227d38fd8fab602f529a3fb79a7a8cc993da5c015c457d901648c6", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-093:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@5a644e4edcc37e5c963e52fda6fab4c85b3ff02e", "material_license": "Apache-2.0; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "b316df2cbcb2bdd50c79216740fcd57b5be0a5aa84ebf5243109d2b3a39e374d", "public_payload_sha256": "fb3d3b3aa1f7da2fc46dd0bf88307fa7ed7ba99e349a4a995f2ffa91d11b340f", "release_id": "093", "repository_url": "https://github.com/Project-MONAI/MONAI", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_093", "title": "Repair a patient-space round trip in MONAI", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-093:v0.1.1@sha256:6378d5a97c239e8867c6a09fd2a07ec026a7abfb0ddd80bb8bae56f8377408b7", "verifier_image_digest": "sha256:6378d5a97c239e8867c6a09fd2a07ec026a7abfb0ddd80bb8bae56f8377408b7", "verifier_image_id": "sha256:6378d5a97c239e8867c6a09fd2a07ec026a7abfb0ddd80bb8bae56f8377408b7", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-093:v0.1.1"}
{"base_commit": "ab97479e8da696b33f02cd140fdd16956600f94a", "domain": "condensed-matter-magnetism-and-magnetic-symmetry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-094:v0.1.1@sha256:26f3e009d815b6edbb6fea7317fc827b0c83ff8239b9faf93d41cd2fde142edd", "environment_image_digest": "sha256:26f3e009d815b6edbb6fea7317fc827b0c83ff8239b9faf93d41cd2fde142edd", "environment_image_id": "sha256:26f3e009d815b6edbb6fea7317fc827b0c83ff8239b9faf93d41cd2fde142edd", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-094:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.rst", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "b34cbcca8f5de06cd097974501b6adc08bfb5d2c28a22b518b316be458f6c55d", "public_payload_sha256": "db57f694d4d5440c3cbeaff3357fad558652f33386edaadba730a0863126e12f", "release_id": "094", "repository_url": "https://github.com/materialsproject/pymatgen", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_094", "title": "Repair magnetic-space-group operations across archived settings", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-094:v0.1.1@sha256:f871bca783e8671572e5c2a95c5e9ce74a5cefdf0fa99298f0514beb63ad5f91", "verifier_image_digest": "sha256:f871bca783e8671572e5c2a95c5e9ce74a5cefdf0fa99298f0514beb63ad5f91", "verifier_image_id": "sha256:f871bca783e8671572e5c2a95c5e9ce74a5cefdf0fa99298f0514beb63ad5f91", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-094:v0.1.1"}
{"base_commit": "d8efaa211ea6721cc4a718890f11fb60b8b43326", "domain": "new-energy-materials", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-095:v0.1.1@sha256:120a6313b6e948cdcacdad8ab115d3c8e65560a71cd0f700859fc531d8aeda79", "environment_image_digest": "sha256:120a6313b6e948cdcacdad8ab115d3c8e65560a71cd0f700859fc531d8aeda79", "environment_image_id": "sha256:120a6313b6e948cdcacdad8ab115d3c8e65560a71cd0f700859fc531d8aeda79", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-095:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "github-api:LICENSE@d8efaa211ea6721cc4a718890f11fb60b8b43326", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "c96fa6a35f1d64bf5328f39c20e058bef62ed246271ce507ca39afc22103c231", "public_payload_sha256": "6ec8718d7ed893b11b2250aac59dc8f4977497cc41395b5fa84f4787c5fdb645", "release_id": "095", "repository_url": "https://github.com/PMEAL/OpenPNM", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_095", "title": "Repair a repeated porous-electrode transport workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-095:v0.1.1@sha256:62f2f24aa3222c0a3a6e3ecee6083aac09591629e44e0582c9952cc44e6cbaf3", "verifier_image_digest": "sha256:62f2f24aa3222c0a3a6e3ecee6083aac09591629e44e0582c9952cc44e6cbaf3", "verifier_image_id": "sha256:62f2f24aa3222c0a3a6e3ecee6083aac09591629e44e0582c9952cc44e6cbaf3", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-095:v0.1.1"}
{"base_commit": "104dfdb64ed00fce6c49a5d67be371f4fca016dd", "domain": "tropical-cyclone-hazard-monitoring", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-096:v0.1.1@sha256:2836db24ab242200c17180cc31bf21859506a70be87b934c5a9e65dd3f2e12a9", "environment_image_digest": "sha256:2836db24ab242200c17180cc31bf21859506a70be87b934c5a9e65dd3f2e12a9", "environment_image_id": "sha256:2836db24ab242200c17180cc31bf21859506a70be87b934c5a9e65dd3f2e12a9", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-096:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "github-api:LICENSE@104dfdb64ed00fce6c49a5d67be371f4fca016dd", "material_license": "CC-BY-4.0; GPL-3.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "c7325fe752ddf486b488aff8c4fff66589c3c181eb8a7ccbc26fa3f0f43e7d6d", "public_payload_sha256": "d3e8a0ced0a9270cb722fb1a5d3c161dbc2747d97b4b1404ef4c1c2a2cdb6dca", "release_id": "096", "repository_url": "https://github.com/CLIMADA-project/climada_python", "restricted_license": true, "restricted_reason": "The retained CLIMADA-derived source is GPL-3.0; explicit restricted-license opt-in is required.", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "GPL-3.0", "status": "dockerhub-published", "task_path": "tasks/task_096", "title": "Repair a wrapped tropical-cyclone hazard workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-096:v0.1.1@sha256:8dbb1d8bae6fcea0585e71a28f019d6daa33026072fcb83cad7cd36ed10cbb94", "verifier_image_digest": "sha256:8dbb1d8bae6fcea0585e71a28f019d6daa33026072fcb83cad7cd36ed10cbb94", "verifier_image_id": "sha256:8dbb1d8bae6fcea0585e71a28f019d6daa33026072fcb83cad7cd36ed10cbb94", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-096:v0.1.1"}
{"base_commit": "6c3b985cbc6e2dec51976a20ae51214186c693b5", "domain": "magnetism-and-spin-models", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-097:v0.1.1@sha256:c60e8430dca0a267be80cd84dc8d3de593009d672d91376c3ee6bc83e686509e", "environment_image_digest": "sha256:c60e8430dca0a267be80cd84dc8d3de593009d672d91376c3ee6bc83e686509e", "environment_image_id": "sha256:c60e8430dca0a267be80cd84dc8d3de593009d672d91376c3ee6bc83e686509e", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-097:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "source/deepmd/utils/spin.py", "material_license": "CC-BY-4.0; LGPL-3.0-or-later", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "e838196db75c682452e2c62d2c7cc2ccc7f64f11334ba13c72f8f1a66da48211", "public_payload_sha256": "ec18cb1d83202c055d537be6f4b8ae3a9caa9a14c1f3e8c397745424dfc3be54", "release_id": "097", "repository_url": "https://github.com/deepmodeling/deepmd-kit", "restricted_license": true, "restricted_reason": "The retained DeePMD-derived source is LGPL-3.0-or-later; explicit restricted-license opt-in is required.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-3.0-or-later", "status": "dockerhub-published", "task_path": "tasks/task_097", "title": "Repair spin-model consistency in DeePMD-kit", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-097:v0.1.1@sha256:12cbdb609f7316d4fa2700879bdbaedfb066aa2df6f0a4a5a8686204efa152c2", "verifier_image_digest": "sha256:12cbdb609f7316d4fa2700879bdbaedfb066aa2df6f0a4a5a8686204efa152c2", "verifier_image_id": "sha256:12cbdb609f7316d4fa2700879bdbaedfb066aa2df6f0a4a5a8686204efa152c2", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-097:v0.1.1"}
{"base_commit": "0ef189634030bda38bd069de30b60f8769995050", "domain": "remote-sensing-and-geostationary-geolocation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-098:v0.1.1@sha256:252cab1364a6acd4b85cda12c1fe685d7a53469a8a7d234d8bfa8d765c7fd196", "environment_image_digest": "sha256:252cab1364a6acd4b85cda12c1fe685d7a53469a8a7d234d8bfa8d765c7fd196", "environment_image_id": "sha256:252cab1364a6acd4b85cda12c1fe685d7a53469a8a7d234d8bfa8d765c7fd196", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-098:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "source/satpy/utils.py", "material_license": "GPL-3.0-or-later; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "b8e9050b896670f76ac2bababc5fdab1cfbe9c007330b93c8d3e8a03a93384c4", "public_payload_sha256": "452b6321fe1f4b2be7f0db5dc4a4db0128b6a61e89008469c125413a907beb94", "release_id": "098", "repository_url": "https://github.com/pytroll/satpy", "restricted_license": true, "restricted_reason": "The retained Satpy-derived source is GPL-3.0-or-later; explicit restricted-license opt-in is required.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "GPL-3.0-or-later", "status": "dockerhub-published", "task_path": "tasks/task_098", "title": "Repair inconsistent satellite parallax geolocation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-098:v0.1.1@sha256:55b18bf0203de35a647f1cb292cf10b6381429a77a9858bd90bf79701a0ada0a", "verifier_image_digest": "sha256:55b18bf0203de35a647f1cb292cf10b6381429a77a9858bd90bf79701a0ada0a", "verifier_image_id": "sha256:55b18bf0203de35a647f1cb292cf10b6381429a77a9858bd90bf79701a0ada0a", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-098:v0.1.1"}
{"base_commit": "9a4e467ba06e636ffa4de6ceee302cefee8b2a34", "domain": "satellite-navigation-and-gnss-positioning", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-099:v0.1.1@sha256:563897f4b3aa7227f4b9e12d95a8d693270fc9d2111378e26356ccb6da107dac", "environment_image_digest": "sha256:563897f4b3aa7227f4b9e12d95a8d693270fc9d2111378e26356ccb6da107dac", "environment_image_id": "sha256:563897f4b3aa7227f4b9e12d95a8d693270fc9d2111378e26356ccb6da107dac", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-099:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": "MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "6836fba6d5391351ba01aebae0abce6b8e84988d3ce236c45528cc391ba09bce", "public_payload_sha256": "3fe79829cea06522823e3be66ee0bb157bdeecce33b727fef7094dbb49ef8ea2", "release_id": "099", "repository_url": "https://github.com/Stanford-NavLab/gnss_lib_py", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_099", "title": "Repair an inconsistent GNSS point solution", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-099:v0.1.1@sha256:bbdc0225f7b4fd0b619b748d21fa7fd6086680e450f009335605b4227ce23ab0", "verifier_image_digest": "sha256:bbdc0225f7b4fd0b619b748d21fa7fd6086680e450f009335605b4227ce23ab0", "verifier_image_id": "sha256:bbdc0225f7b4fd0b619b748d21fa7fd6086680e450f009335605b4227ce23ab0", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-099:v0.1.1"}
{"base_commit": "c2f22341f2b1eb2f619b76534cf4abe2e5e6b3a3", "domain": "reticular-chemistry-and-framework-geometry", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-100:v0.1.1@sha256:ce5a12e15a2211231007cd784d006ef315f7f9a568856099658328eba8fe00bf", "environment_image_digest": "sha256:ce5a12e15a2211231007cd784d006ef315f7f9a568856099658328eba8fe00bf", "environment_image_id": "sha256:ce5a12e15a2211231007cd784d006ef315f7f9a568856099658328eba8fe00bf", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-100:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "COPYING", "material_license": "LGPL-2.1-family and MIT (upstream conflict); MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "04e51ce99b0e2aa879dfdbb5e5b5bcc9599440b9193bcbcbe6c57e8f0908c487", "public_payload_sha256": "272b2765c1f70523a2609be4aee6a938e3d610f3cfe5816b197396482511b3da", "release_id": "100", "repository_url": "https://github.com/DCoupry/autografs", "restricted_license": true, "restricted_reason": "The upstream AuToGraFS snapshot has unresolved LGPL-2.1 versus MIT declarations; only the retained code and independently generated synthetic data are distributed under explicit restricted opt-in.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "LGPL-2.1-family and MIT (upstream conflict)", "status": "dockerhub-published", "task_path": "tasks/task_100", "title": "Repair calibrated framework embedding relaxation", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-100:v0.1.1@sha256:f31d5844bc55cf997b84e2518c2a71c0daf1c09292fca7285fb42348787489b6", "verifier_image_digest": "sha256:f31d5844bc55cf997b84e2518c2a71c0daf1c09292fca7285fb42348787489b6", "verifier_image_id": "sha256:f31d5844bc55cf997b84e2518c2a71c0daf1c09292fca7285fb42348787489b6", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-100:v0.1.1"}
{"base_commit": "1e9fbcea25b78a0a633face62b077dae1f92bf62", "domain": "lithium-ion-battery-modeling", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-101:v0.1.1@sha256:5a10c1cc642f417aed2e1478484a2177a7e5c98efb3cd57acba8b8d73adf021c", "environment_image_digest": "sha256:5a10c1cc642f417aed2e1478484a2177a7e5c98efb3cd57acba8b8d73adf021c", "environment_image_id": "sha256:5a10c1cc642f417aed2e1478484a2177a7e5c98efb3cd57acba8b8d73adf021c", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-101:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "restricted-materials", "license_source": "LICENSE.txt", "material_license": "BSD-3-Clause; CC-BY-4.0; CC-BY-NC-ND-4.0", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "c64ced25c2a46f3486fe60f606d7684febb4adc983ecae35bdc92543528c7eb4", "public_payload_sha256": "16dc3155055489b5b9ef1a9592d71ccb213c280eb10993c011234d6bec265d6e", "release_id": "101", "repository_url": "https://github.com/pybamm-team/PyBaMM", "restricted_license": true, "restricted_reason": "The required Chen2020 parameter CSVs are derived from a CC-BY-NC-ND article; explicit restricted-material opt-in is required.", "schema_version": 1, "science_knowledge_ablation": true, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_101", "title": "Repair an inconsistent battery-model reproduction", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-101:v0.1.1@sha256:351e46f543c558cf41d5ac880353cee71632002cae6f9fabe07c543b9ae9e63e", "verifier_image_digest": "sha256:351e46f543c558cf41d5ac880353cee71632002cae6f9fabe07c543b9ae9e63e", "verifier_image_id": "sha256:351e46f543c558cf41d5ac880353cee71632002cae6f9fabe07c543b9ae9e63e", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-101:v0.1.1"}
{"base_commit": "160e9707d844ad1b108e1d8184152050d16088a0", "domain": "polymer-coordinate-generation", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-102:v0.1.1@sha256:7fbf7db1c42d467e46571678176734ebddebf9b7851c837580a2b51a99cf4cb0", "environment_image_digest": "sha256:7fbf7db1c42d467e46571678176734ebddebf9b7851c837580a2b51a99cf4cb0", "environment_image_id": "sha256:7fbf7db1c42d467e46571678176734ebddebf9b7851c837580a2b51a99cf4cb0", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-102:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "restricted-materials", "license_source": "LICENSE", "material_license": "Apache-2.0; CC-BY-4.0; LicenseRef-2016H66-Redistribution-Unverified", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": true, "materials_gate": true, "materials_manifest_sha256": "ee3eca49b12a932bc4e0f2a4643371cf5f35bb018cb8362267d39b6533195e2f", "public_payload_sha256": "c0ed91c3b8f1c639ea4f0e48ecec0349e4975f242af2c3ebdf8510e86fb9dda6", "release_id": "102", "repository_url": "https://github.com/marrink-lab/polyply_1.0", "restricted_license": true, "restricted_reason": "The retained 2016H66 force-field records have no complete per-file redistribution grant; explicit restricted-material opt-in is required.", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "Apache-2.0", "status": "dockerhub-published", "task_path": "tasks/task_102", "title": "Repair an inconsistent polymer coordinate workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-102:v0.1.1@sha256:adaf1de19b5892112a68f14183079fe298592287c6744d336bcc08997b95b336", "verifier_image_digest": "sha256:adaf1de19b5892112a68f14183079fe298592287c6744d336bcc08997b95b336", "verifier_image_id": "sha256:adaf1de19b5892112a68f14183079fe298592287c6744d336bcc08997b95b336", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-102:v0.1.1"}
{"base_commit": "bdff2bb616847a058960c56328b68e36ab3764e3", "domain": "high-performance-fibers-and-composites", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-103:v0.1.1@sha256:dc47445186c6d021cb6cc81f34fe4702c822a6c4b4ecd18f66580aca22a967e5", "environment_image_digest": "sha256:dc47445186c6d021cb6cc81f34fe4702c822a6c4b4ecd18f66580aca22a967e5", "environment_image_id": "sha256:dc47445186c6d021cb6cc81f34fe4702c822a6c4b4ecd18f66580aca22a967e5", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-103:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.md", "material_license": "BSD-3-Clause; US-Government-Public-Use", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "e6d9d41ed7a153e4c817aede1aa102cf9e553da0c79f9d6cff217afaf596de52", "public_payload_sha256": "3abc1d145b5ab09ad2e2f9c5f39066e07c7719305b15ddeff5e742c6e4095d59", "release_id": "103", "repository_url": "https://github.com/SteveDoyle2/pyNastran", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_103", "title": "Repair symmetric composite laminate ABD calculations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-103:v0.1.1@sha256:f5aee22839b572d8edf7c7884c1473cca47f07ee681bd11309ad3fd71d26c6dc", "verifier_image_digest": "sha256:f5aee22839b572d8edf7c7884c1473cca47f07ee681bd11309ad3fd71d26c6dc", "verifier_image_id": "sha256:f5aee22839b572d8edf7c7884c1473cca47f07ee681bd11309ad3fd71d26c6dc", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-103:v0.1.1"}
{"base_commit": "4cf09f36bb4afb42c661e8765e14b4527581eff7", "domain": "energy-materials-and-finite-volume-transport", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-104:v0.1.1@sha256:ce9d9e97837da59051b4fe3e75705b4f1825c41f8f0c08314c2a866603a4ebdf", "environment_image_digest": "sha256:ce9d9e97837da59051b4fe3e75705b4f1825c41f8f0c08314c2a866603a4ebdf", "environment_image_id": "sha256:ce9d9e97837da59051b4fe3e75705b4f1825c41f8f0c08314c2a866603a4ebdf", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-104:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": "BSD-3-Clause; MIT", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "49f991ef7ff6992887975d17ab7b62501cb13c053d31c3a8e64b4bbde2c4f384", "public_payload_sha256": "d63989bb4f4cecf4b24843b304b49436744d217faa6da6ea512375b3891d3529", "release_id": "104", "repository_url": "https://github.com/pybamm-team/PyBaMM", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_104", "title": "Repair inconsistent finite-volume advection edge states", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-104:v0.1.1@sha256:4e3e0fbde6106146ebadaecb511695588c4e06dec6a71b0bfac4c8de994bd2bc", "verifier_image_digest": "sha256:4e3e0fbde6106146ebadaecb511695588c4e06dec6a71b0bfac4c8de994bd2bc", "verifier_image_id": "sha256:4e3e0fbde6106146ebadaecb511695588c4e06dec6a71b0bfac4c8de994bd2bc", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-104:v0.1.1"}
{"base_commit": "313bed48f942a3663e2dc496f4e930dacbbcf8aa", "domain": "drug-discovery-cheminformatics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-cpp-task-105:v0.1.1@sha256:721d5d82c06dc94311745b3c5bf40ed1903f8c44085320e2237d79799bce70ac", "environment_image_digest": "sha256:721d5d82c06dc94311745b3c5bf40ed1903f8c44085320e2237d79799bce70ac", "environment_image_id": "sha256:721d5d82c06dc94311745b3c5bf40ed1903f8c44085320e2237d79799bce70ac", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-cpp-task-105:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python-cpp", "license_gate": "none", "license_source": "license.txt", "material_license": "BSD-3-Clause; BSL-1.0; No article redistribution grant asserted", "material_license_source": "environment/public/MATERIALS.json", "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": "9805568c294fa9dfcb24b4787be10abb1f5590bdd1e8bacf737636b808625c41", "public_payload_sha256": "c29070a194706b7874d225690e69ce2f6428e8c2397f352186c5817304df1424", "release_id": "105", "repository_url": "https://github.com/rdkit/rdkit", "restricted_license": false, "restricted_reason": "", "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_105", "title": "Restore a stereo-preserving tautomer workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cpp-task-105:v0.1.1@sha256:4e96032a9972da65b1146cc41f8332bda8b16276b7ebf50db8287d5d7a434a96", "verifier_image_digest": "sha256:4e96032a9972da65b1146cc41f8332bda8b16276b7ebf50db8287d5d7a434a96", "verifier_image_id": "sha256:4e96032a9972da65b1146cc41f8332bda8b16276b7ebf50db8287d5d7a434a96", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-cpp-task-105:v0.1.1"}
{"base_commit": "839001468ba8f8da64ba9d54b33fa33c795ed3c5", "domain": "chemoinformatics-molecular-fingerprints", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-106:v0.1.1@sha256:d55e2bb845c86d2f543f6f92ef5d4d006d3effcd8babd92272c5611b39cc8474", "environment_image_digest": "sha256:d55e2bb845c86d2f543f6f92ef5d4d006d3effcd8babd92272c5611b39cc8474", "environment_image_id": "sha256:d55e2bb845c86d2f543f6f92ef5d4d006d3effcd8babd92272c5611b39cc8474", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-106:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.md", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "8a48e92bef8f58abd989ac90579702fbc6f45bf17524a566519fc03ae10381b2", "release_id": "106", "repository_url": "https://github.com/MLCIL/scikit-fingerprints", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_106", "title": "Reproduce and extend a version-pinned MAP4/MAPC retrieval protocol", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-106:v0.1.1@sha256:2c7ddddb4e5595efd5421461fffab8a15fd94618104523a27a6f3bbba6e71a26", "verifier_image_digest": "sha256:2c7ddddb4e5595efd5421461fffab8a15fd94618104523a27a6f3bbba6e71a26", "verifier_image_id": "sha256:2c7ddddb4e5595efd5421461fffab8a15fd94618104523a27a6f3bbba6e71a26", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-106:v0.1.1"}
{"base_commit": "afe8935530a61ae5bd7a90400fa60c0d2c8c18a4", "domain": "computer-algebra", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-107:v0.1.1@sha256:d9bed5d007500d41681c6eda3250cf3431fc7b20c875a6722791de9f89239ddc", "environment_image_digest": "sha256:d9bed5d007500d41681c6eda3250cf3431fc7b20c875a6722791de9f89239ddc", "environment_image_id": "sha256:d9bed5d007500d41681c6eda3250cf3431fc7b20c875a6722791de9f89239ddc", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-107:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "7289cadcad260050c6f6b06bef9338b78fd2fcf9820b537ebcd8cbe7508e76e2", "release_id": "107", "repository_url": "https://github.com/sympy/sympy", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_107", "title": "Repair a public symbolic workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-107:v0.1.1@sha256:1a5c67f1817c05b93066b554f6b83f498f73f1b610ee8ea13507c0b475e96bfd", "verifier_image_digest": "sha256:1a5c67f1817c05b93066b554f6b83f498f73f1b610ee8ea13507c0b475e96bfd", "verifier_image_id": "sha256:1a5c67f1817c05b93066b554f6b83f498f73f1b610ee8ea13507c0b475e96bfd", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-107:v0.1.1"}
{"base_commit": "5e683847c782a4c38ec71b8a88e6b1fbd903548f", "domain": "computational-mathematics-special-functions", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-108:v0.1.1@sha256:e281e4d9df4e2047e90a84393c8623e2e492578b722cc7970792da35f4f7ee02", "environment_image_digest": "sha256:e281e4d9df4e2047e90a84393c8623e2e492578b722cc7970792da35f4f7ee02", "environment_image_id": "sha256:e281e4d9df4e2047e90a84393c8623e2e492578b722cc7970792da35f4f7ee02", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-108:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "8d1de7758a3b42c81d789060af785ad55c41f5807c2e7ad6498642a81a79d32c", "release_id": "108", "repository_url": "https://github.com/mpmath/mpmath", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_108", "title": "Restore stable Jacobi theta evaluations across difficult regimes", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-108:v0.1.1@sha256:8db765c589aa1c821ac3e5cde3dc2f13dadf41c35132bda6e7ee121254e8f73a", "verifier_image_digest": "sha256:8db765c589aa1c821ac3e5cde3dc2f13dadf41c35132bda6e7ee121254e8f73a", "verifier_image_id": "sha256:8db765c589aa1c821ac3e5cde3dc2f13dadf41c35132bda6e7ee121254e8f73a", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-108:v0.1.1"}
{"base_commit": "e81538d9a2ab5031559d0dd74b742ded5465406c", "domain": "high-performance-fibers-and-composites", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-109:v0.1.1@sha256:464a6f95fbc6d919248b77f9ed7a2d403b2120705ea1be6d0390656fe93d2e89", "environment_image_digest": "sha256:464a6f95fbc6d919248b77f9ed7a2d403b2120705ea1be6d0390656fe93d2e89", "environment_image_id": "sha256:464a6f95fbc6d919248b77f9ed7a2d403b2120705ea1be6d0390656fe93d2e89", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-109:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "2afe128e08664e390363141a916dc8bedf1fac33c7ae2d80a61a530109ff70da", "release_id": "109", "repository_url": "https://github.com/elhajjar1/wrinkleFE", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_109", "title": "Repair paired wrinkle FE analysis", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-109:v0.1.1@sha256:b8c2d6a3e9d319f7cb3294afe63976c1bad693e90e7d01980eb7c0c4720cb545", "verifier_image_digest": "sha256:b8c2d6a3e9d319f7cb3294afe63976c1bad693e90e7d01980eb7c0c4720cb545", "verifier_image_id": "sha256:b8c2d6a3e9d319f7cb3294afe63976c1bad693e90e7d01980eb7c0c4720cb545", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-109:v0.1.1"}
{"base_commit": "2d6248fff963c2eb4a69999e8c6478e37fc35ce7", "domain": "high-performance-fibers-and-composites", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-110:v0.1.1@sha256:d333778e80f42ff762176b89492005dfda8cbe680067bfdf417d82751b18da4f", "environment_image_digest": "sha256:d333778e80f42ff762176b89492005dfda8cbe680067bfdf417d82751b18da4f", "environment_image_id": "sha256:d333778e80f42ff762176b89492005dfda8cbe680067bfdf417d82751b18da4f", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-110:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "43b01abaa46b919c07d923a122af95ecab6053e59178a3a3bd3487ac3c9aa154", "release_id": "110", "repository_url": "https://github.com/robbievanleeuwen/section-properties", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_110", "title": "Restore consistent cross-section analysis results", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-110:v0.1.1@sha256:c0a222690f44ab8ca6aebb45094ece6132c681a7e907f912ab730803fb3f2f34", "verifier_image_digest": "sha256:c0a222690f44ab8ca6aebb45094ece6132c681a7e907f912ab730803fb3f2f34", "verifier_image_id": "sha256:c0a222690f44ab8ca6aebb45094ece6132c681a7e907f912ab730803fb3f2f34", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-110:v0.1.1"}
{"base_commit": "46ad665fb84bda0c2d9b3392b6f2ef2388af1358", "domain": "computational-mechanics-and-soft-filament-dynamics", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-111:v0.1.1@sha256:be8c842c4fba5e9c69f6d81194b99c9bb496b90d271cf9c1f89c8219ea069e96", "environment_image_digest": "sha256:be8c842c4fba5e9c69f6d81194b99c9bb496b90d271cf9c1f89c8219ea069e96", "environment_image_id": "sha256:be8c842c4fba5e9c69f6d81194b99c9bb496b90d271cf9c1f89c8219ea069e96", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-111:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "70dacf5c7dd98f526b9429978c8d18d6af1a0aab5d4285836b3df3ba92db3633", "release_id": "111", "repository_url": "https://github.com/GazzolaLab/PyElastica", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_111", "title": "Restore consistent tapered-filament free response", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-111:v0.1.1@sha256:d1f89ef44d00ba6a6d86fbd9c38160846d3925cfd06982d4d11f745c2e43d4e6", "verifier_image_digest": "sha256:d1f89ef44d00ba6a6d86fbd9c38160846d3925cfd06982d4d11f745c2e43d4e6", "verifier_image_id": "sha256:d1f89ef44d00ba6a6d86fbd9c38160846d3925cfd06982d4d11f745c2e43d4e6", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-111:v0.1.1"}
{"base_commit": "cee66acea267c69839f7970bb771abdb4f86c1a1", "domain": "high-performance-fibers-and-composites", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-112:v0.1.1@sha256:e9fff7cdcc27279c147d4d82acf72318aa2f79d429cb66447b17e7f574d02066", "environment_image_digest": "sha256:e9fff7cdcc27279c147d4d82acf72318aa2f79d429cb66447b17e7f574d02066", "environment_image_id": "sha256:e9fff7cdcc27279c147d4d82acf72318aa2f79d429cb66447b17e7f574d02066", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-112:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "0d7a8774d275b195ba48384b810348d05e655c1146545195c51934805209fc9a", "release_id": "112", "repository_url": "https://github.com/robbievanleeuwen/section-properties", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_112", "title": "Repair an inconsistent hybrid-section plastic capacity workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-112:v0.1.1@sha256:ef1e5aac750fc5146793f1e1410b13fb6219a12acac82405f51cbb34194c4cee", "verifier_image_digest": "sha256:ef1e5aac750fc5146793f1e1410b13fb6219a12acac82405f51cbb34194c4cee", "verifier_image_id": "sha256:ef1e5aac750fc5146793f1e1410b13fb6219a12acac82405f51cbb34194c4cee", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-112:v0.1.1"}
{"base_commit": "339e6aae28a11f39a2e18bbf110fc368e18b1e72", "domain": "renewable-energy-modelling", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-113:v0.1.1@sha256:27948b4162e6d4c2d60b3408e418af6459c02c5a2019d5509bf3aca7169f88a8", "environment_image_digest": "sha256:27948b4162e6d4c2d60b3408e418af6459c02c5a2019d5509bf3aca7169f88a8", "environment_image_id": "sha256:27948b4162e6d4c2d60b3408e418af6459c02c5a2019d5509bf3aca7169f88a8", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-113:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "cdacc738ffce716f5d5fa2f3c5e79d91eb6fa85679ab2dd28d53cc1d3b7566da", "release_id": "113", "repository_url": "https://github.com/pvlib/pvlib-python", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_113", "title": "Repair an inconsistent solar-resource workflow", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-113:v0.1.1@sha256:5ace611a3ae59ae06d6bb2a4b4de17b1c38f57bf50a1f5096e8c6947dce5d758", "verifier_image_digest": "sha256:5ace611a3ae59ae06d6bb2a4b4de17b1c38f57bf50a1f5096e8c6947dce5d758", "verifier_image_id": "sha256:5ace611a3ae59ae06d6bb2a4b4de17b1c38f57bf50a1f5096e8c6947dce5d758", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-113:v0.1.1"}
{"base_commit": "895bc26c721abbb826d7f8caf51587a66c69f15d", "domain": "power-system-energy-storage", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-114:v0.1.1@sha256:98917b9e6946f2d0f7d30f90a830d8b23b7af66737be921a84b5f73385378d29", "environment_image_digest": "sha256:98917b9e6946f2d0f7d30f90a830d8b23b7af66737be921a84b5f73385378d29", "environment_image_id": "sha256:98917b9e6946f2d0f7d30f90a830d8b23b7af66737be921a84b5f73385378d29", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-114:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE.txt", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "0c2b2a038150153ce990d7d208312c2aa71d2981121f41783bcb7c014ce966c8", "release_id": "114", "repository_url": "https://github.com/PyPSA/PyPSA", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": true, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_114", "title": "Repair an implausible storage history at a planning-epoch boundary", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-114:v0.1.1@sha256:61dde7a057773f55e54e42b3806cbfa9f958e12bd722fd4b267e630c84e7e6fa", "verifier_image_digest": "sha256:61dde7a057773f55e54e42b3806cbfa9f958e12bd722fd4b267e630c84e7e6fa", "verifier_image_id": "sha256:61dde7a057773f55e54e42b3806cbfa9f958e12bd722fd4b267e630c84e7e6fa", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-114:v0.1.1"}
{"base_commit": "147c7aa24ec30b1c6a4d4820446915380752877b", "domain": "structural-engineering-and-disaster-resilience", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-115:v0.1.1@sha256:318a403ff630580e57ad4d6f1a6da837a8b1011909004bb4e3a2c2052e7946da", "environment_image_digest": "sha256:318a403ff630580e57ad4d6f1a6da837a8b1011909004bb4e3a2c2052e7946da", "environment_image_id": "sha256:318a403ff630580e57ad4d6f1a6da837a8b1011909004bb4e3a2c2052e7946da", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-115:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "b40c8ca383e4c68713c3d0d999f53413bc548496715b9a132637db9ba7414dea", "release_id": "115", "repository_url": "https://github.com/JWock82/Pynite", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_115", "title": "Restore physically meaningful structural stability checks", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-115:v0.1.1@sha256:1b16ce929f12ec92e01fef2775b3ab0d9d96346c3b1a8362ab9559fecc4871f0", "verifier_image_digest": "sha256:1b16ce929f12ec92e01fef2775b3ab0d9d96346c3b1a8362ab9559fecc4871f0", "verifier_image_id": "sha256:1b16ce929f12ec92e01fef2775b3ab0d9d96346c3b1a8362ab9559fecc4871f0", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-115:v0.1.1"}
{"base_commit": "147c7aa24ec30b1c6a4d4820446915380752877b", "domain": "structural-engineering-finite-element-resilience", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-116:v0.1.1@sha256:919fdbc765237cfeebcada9836f4dafb7b54e2838381867da82911bf706c3473", "environment_image_digest": "sha256:919fdbc765237cfeebcada9836f4dafb7b54e2838381867da82911bf706c3473", "environment_image_id": "sha256:919fdbc765237cfeebcada9836f4dafb7b54e2838381867da82911bf706c3473", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-116:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "d303f1c6ce0e8937c822814863a006b6eaa1ee13e56843656713c67d6028abca", "release_id": "116", "repository_url": "https://github.com/JWock82/Pynite", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_116", "title": "Repair mode-dependent structural analysis observations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-116:v0.1.1@sha256:18362993ba38c4a6981c386934b43733bdf13d5d3792b5952b3762ff420be98e", "verifier_image_digest": "sha256:18362993ba38c4a6981c386934b43733bdf13d5d3792b5952b3762ff420be98e", "verifier_image_id": "sha256:18362993ba38c4a6981c386934b43733bdf13d5d3792b5952b3762ff420be98e", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-116:v0.1.1"}
{"base_commit": "573e51689fe5fe54f279a7a875e431a35355fe73", "domain": "structural-engineering-disaster-resilience", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-117:v0.1.1@sha256:19952242ad26d8ec83451ad087d3e37b36cbe9c87312b37f3e8f6020b150dafe", "environment_image_digest": "sha256:19952242ad26d8ec83451ad087d3e37b36cbe9c87312b37f3e8f6020b150dafe", "environment_image_id": "sha256:19952242ad26d8ec83451ad087d3e37b36cbe9c87312b37f3e8f6020b150dafe", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-117:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "5a7cba20f99d10301680be877801376105a80b41b439e0dbc12187f40774b4ab", "release_id": "117", "repository_url": "https://github.com/JWock82/Pynite", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "MIT", "status": "dockerhub-published", "task_path": "tasks/task_117", "title": "Repair inconsistent lateral-frame member observations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-117:v0.1.1@sha256:5c9d6aac4d7a4480cb2591fea878ea1d6c323bdd0571f2a0b9d88bbe3d0474b9", "verifier_image_digest": "sha256:5c9d6aac4d7a4480cb2591fea878ea1d6c323bdd0571f2a0b9d88bbe3d0474b9", "verifier_image_id": "sha256:5c9d6aac4d7a4480cb2591fea878ea1d6c323bdd0571f2a0b9d88bbe3d0474b9", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-117:v0.1.1"}
{"base_commit": "2201589812172b25c515ad502c3607d1e2c65a92", "domain": "computational-high-energy-molecular-chemistry-periodic-models", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-118:v0.1.1@sha256:1be2825014bb2ea8415da827d416e7beb90d46d85a44e6bf3009cb0fdb3db0cc", "environment_image_digest": "sha256:1be2825014bb2ea8415da827d416e7beb90d46d85a44e6bf3009cb0fdb3db0cc", "environment_image_id": "sha256:1be2825014bb2ea8415da827d416e7beb90d46d85a44e6bf3009cb0fdb3db0cc", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-118:v0.1.1", "gpl_family": true, "image_platform": "linux/amd64", "language": "python", "license_gate": "gpl-family", "license_source": "COPYING.LESSER", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "c8977cfc918310e5186ed40608c858b2c6bab8c47f0d50f4948f4fc9f34105b1", "release_id": "118", "repository_url": "https://github.com/tblite/tblite", "restricted_license": true, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "LGPL-3.0-or-later", "status": "dockerhub-published", "task_path": "tasks/task_118", "title": "Repair inconsistent periodic molecular energy representations", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-118:v0.1.1@sha256:d9d994d83ed59efa74d512e9306ed84d990a37a00d7ce444e2b6738b124914fd", "verifier_image_digest": "sha256:d9d994d83ed59efa74d512e9306ed84d990a37a00d7ce444e2b6738b124914fd", "verifier_image_id": "sha256:d9d994d83ed59efa74d512e9306ed84d990a37a00d7ce444e2b6738b124914fd", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-118:v0.1.1"}
{"base_commit": "dd5eec6bfefa11ffe0ec81e2c4018003e8e39f2b", "domain": "quantum-chemistry-reaction-paths", "environment_image": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-119:v0.1.1@sha256:2259431fe6b24ca89cb78517fc0882c2143c9bc1eb1846a3cb451b43d3eae3b5", "environment_image_digest": "sha256:2259431fe6b24ca89cb78517fc0882c2143c9bc1eb1846a3cb451b43d3eae3b5", "environment_image_id": "sha256:2259431fe6b24ca89cb78517fc0882c2143c9bc1eb1846a3cb451b43d3eae3b5", "environment_image_tag": "docker.io/kevinxulearning/swe-bench-science-environment-python-task-119:v0.1.1", "gpl_family": false, "image_platform": "linux/amd64", "language": "python", "license_gate": "none", "license_source": "LICENSE", "material_license": null, "material_license_source": null, "material_restricted": false, "materials_gate": false, "materials_manifest_sha256": null, "public_payload_sha256": "24f944bb0d203d04b8ea9a220c3242c901c034b9aef828168ef4bbd22d198bfd", "release_id": "119", "repository_url": "https://github.com/MolSSI/QCEngine", "restricted_license": false, "restricted_reason": null, "schema_version": 1, "science_knowledge_ablation": false, "source_license": "BSD-3-Clause", "status": "dockerhub-published", "task_path": "tasks/task_119", "title": "Repair a molecular curvature workflow for reaction-path analysis", "verifier_image": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-119:v0.1.1@sha256:2e5b8b443c3eb07bc0d543ee9d65e2565b3d6e0cd9e3193043e0f9c221ca4d2f", "verifier_image_digest": "sha256:2e5b8b443c3eb07bc0d543ee9d65e2565b3d6e0cd9e3193043e0f9c221ca4d2f", "verifier_image_id": "sha256:2e5b8b443c3eb07bc0d543ee9d65e2565b3d6e0cd9e3193043e0f9c221ca4d2f", "verifier_image_tag": "docker.io/kevinxulearning/swe-bench-science-verifier-python-task-119:v0.1.1"}