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"claims": [
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"control_artifacts": [
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"destructive_control": true,
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"destructive_or_boundary_control": "Deleting the train/test nonemptiness correction changes the m=3,d=4,b=2 count and is detected.",
"evidence_tier": "literal_claim_experiment",
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"outputs/results.json"
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"independent_oracle": "The direct Cartesian-state enumerator shares no combinatorial closed form with the equation path; the released repository independently supplies the thirteen Model-Unlearning model choices.",
"limitation": "This exact conclusion concerns the registered combinatorial construction and does not estimate downstream agent quality.",
"literal_claim": "DiscoGen procedurally generates over 400 million distinct algorithm discovery tasks via a combinatorial formula N_tasks = 2*3*b*(2^m-1)*(3^d-2^(d+1)+1) depending on the number of modules m, datasets d, and backends b (Section 4.2, Equation 1).",
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"paper_or_released_scale": true,
"registered_system_executed": true,
"result": "All ten reported rows match exactly and sum to 493,355,172; four exhaustive state enumerations match the formula, while omitting the nonempty train/test exclusion overcounts the control.",
"scope_boundary": "The assessment is confined to the exact live claim, arXiv-v1 tables, and official v1.0.0 release.",
"source_locator": "source/primary/sections/5_discogen.tex and source/primary/appendix/9_implementation_details.tex"
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{
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"destructive_control": true,
"destructive_control_executed": true,
"destructive_or_boundary_control": "Removing On-Policy MARL collapses the total below two billion, decisively separating the 99-billion result.",
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"independent_oracle": "The source-table summation and recursive official-repository inventory are independent paths over different artifacts.",
"limitation": "This exact conclusion concerns the registered expanded task-space inventory and does not estimate downstream agent quality.",
"literal_claim": "Including additional domains beyond the main evaluation set, DiscoGen's total task space reaches approximately 99 billion tasks (Appendix C).",
"native_scale_justification": "The complete registered table/configuration object is parsed and recomputed; where released execution exists, the pinned official builder is run directly.",
"not_proxy_reason": "The exact arXiv-v1 registered data, official v1.0.0 configurations, and released task builder are used; no reduced ML benchmark or invented agent run substitutes for them.",
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"paper_or_released_scale": true,
"registered_system_executed": true,
"result": "The fourteen rows sum exactly to 99,299,115,384, and the official repository independently contains 14 domains.",
"scope_boundary": "The assessment is confined to the exact live claim, arXiv-v1 tables, and official v1.0.0 release.",
"source_locator": "source/primary/appendix/16_additional_domains.tex"
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{
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"destructive_or_boundary_control": "Dropping one domain changes the median and is detected.",
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"independent_oracle": "Python integer order statistics recompute the registered summary from all ten parsed primary rows rather than accepting the printed Total/Median lines.",
"limitation": "This exact conclusion concerns all ten registered task-count rows and makes no claim about unregistered domains.",
"literal_claim": "Across the 10 domains used in the main evaluation, per-domain task counts range from 900 (Greenhouse Gas Prediction) to 426,043,800 (On-Policy RL), with a median of 59,622 tasks per domain (Table 1).",
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"not_proxy_reason": "The exact arXiv-v1 registered data, official v1.0.0 configurations, and released task builder are used; no reduced ML benchmark or invented agent run substitutes for them.",
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"paper_or_released_scale": true,
"registered_system_executed": true,
"result": "The executed table has 10 domains, minimum 900 for Greenhouse Gas Prediction, maximum 426,043,800 for On-Policy RL, and median 59,622.",
"scope_boundary": "The assessment is confined to the exact live claim, arXiv-v1 tables, and official v1.0.0 release.",
"source_locator": "source/primary/sections/5_discogen.tex"
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{
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"destructive_or_boundary_control": "Turning on a second module in an official single-module config is rejected by the one-active-module invariant.",
"evidence_tier": "full_pipeline_reproduction",
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"outputs/results.json"
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"replay_a/claim4.json",
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"independent_oracle": "The structural configuration checker independently validates the actual file trees created by the released MakeFiles implementation.",
"limitation": "The execution establishes the released benchmark-construction object; it does not claim a new agent-performance evaluation.",
"literal_claim": "DiscoBench provides a fixed evaluation subset built from DiscoGen, comprising, for each domain, m single-module tasks (DiscoBench Single) plus one comprehensive all-modules-active task (DiscoBench All) (Section 4.4).",
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"not_proxy_reason": "The exact arXiv-v1 registered data, official v1.0.0 configurations, and released task builder are used; no reduced ML benchmark or invented agent run substitutes for them.",
"oracle_artifacts": [
"replay_a/claim4.json",
"replay_b/claim4.json"
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"paper_native_mechanism": "Executes the released v1.0.0 DiscoBench builder on four genuine configurations and checks every official single-module/all-modules YAML against its domain schema.",
"paper_or_released_scale": true,
"registered_system_executed": true,
"result": "All 74 released m+1 configurations pass with zero failures; four official builds materialize 82 code/description files at tree digest 88d6c144caefdba3dfbb41aa7247ce4364a7e26928fe4010f51806321a29522c.",
"scope_boundary": "The assessment is confined to the exact live claim, arXiv-v1 tables, and official v1.0.0 release.",
"source_locator": "source/discogen-v1.0.0.tar.gz; official create_discobench.py and discobench_configs/"
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{
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"control_artifacts": [
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"destructive_or_boundary_control": "Reversing every model's success sequence makes the monotonic-decline test fail.",
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"outputs/results.json"
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"independent_oracle": "The 15 combinations are regenerated independently from the four registered modules and matched to the complete primary result table.",
"limitation": "The verdict is limited to the complete registered Appendix-G sweep and does not extrapolate to unreported checkpoints or domains.",
"literal_claim": "As the number of editable modules increases in DiscoBench tasks, agent success rates consistently decline while the achievable performance ceiling rises (Appendix G).",
"native_scale_justification": "The complete registered table/configuration object is parsed and recomputed; where released execution exists, the pinned official builder is run directly.",
"not_proxy_reason": "The exact arXiv-v1 registered data, official v1.0.0 configurations, and released task builder are used; no reduced ML benchmark or invented agent run substitutes for them.",
"oracle_artifacts": [
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"paper_native_mechanism": "Parses the complete Appendix-G 15-configuration On-Policy-RL sweep, reconstructs all four module-combination levels, and recomputes success monotonicity and per-environment ceilings.",
"paper_or_released_scale": true,
"rate_artifact": "outputs/claim5.json",
"rate_evidence_mode": "empirical_scaling",
"rate_executed_system": true,
"rate_fit_claim_consistent": true,
"rate_fit_slope": -17.73666666666668,
"rate_horizons": [
1,
2,
3,
4
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"rate_measurement": "Complete primary success-rate means by module count are [51.4, 28.7, 5.533333, 0.0]; all three model rows are independently monotone nonincreasing.",
"rate_repetitions_per_horizon": 3,
"registered_system_executed": true,
"result": "All three model success sequences are nonincreasing from one to four editable modules. The mean four-environment ceiling rises from 99.3475 to 108.3300 (+8.9825), with higher two-module maxima in 3/4 environments.",
"scope_boundary": "The assessment is confined to the exact live claim, arXiv-v1 tables, and official v1.0.0 release.",
"source_locator": "source/primary/appendix/7_onpolicyresults.tex"
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"status": "pass_full_credit_direct_native_and_complete_primary_data",
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