| --- |
| pretty_name: XV-ML full-ledger paper classification |
| tags: |
| - papers |
| - machine-learning |
| - research-metadata |
| - provenance |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/*.parquet |
| - config_name: curated_references |
| data_files: |
| - split: train |
| path: coverage/references.parquet |
| - config_name: review_candidates |
| data_files: |
| - split: train |
| path: review/data/*.parquet |
| --- |
| |
| # XV-ML full-ledger paper classification |
|
|
| This is the `modelomics/xv-ml` release, generated from a captured full-ledger pass. |
| Release `modelome-xv-ml-2026-10-08` is `complete and ready for release`. The manifest is the source of runtime |
| totals; this card does not invent counts or describe an incomplete manifest as |
| published. The direct dataset is [modelomics/xv-ml](https://huggingface.co/datasets/modelomics/xv-ml). |
|
|
| The capture is bounded by the recorded live-ledger high-water mark. It is a |
| full pass over that current ledger with curated supplements, not a global |
| coverage claim; unresolved source gaps remain possible. |
|
|
| ## Storage and counts |
|
|
| Parquet files use the canonical `train` storage split. This is a storage name, |
| not a training/evaluation benchmark claim. |
|
|
| | Measure | Rows | |
| | --- | ---: | |
| | `classifier_included` | 1530803 | |
| | `curated_only` | 2047 | |
| | `examined_rows` | 33323692 | |
| | `included_rows` | 1532850 | |
| | `review_rows` | 8429993 | |
| | `runner_included_rows` | 9960930 | |
| | `scored_rows` | 33313758 | |
|
|
| | Source | Rows | |
| | --- | ---: | |
| | `acl-test-of-time` | 13 | |
| | `arxiv-complete-snapshot` | 700358 | |
| | `biorxiv` | 2832 | |
| | `crossref` | 34183 | |
| | `crossref-public-data` | 56 | |
| | `cvpr-longuet-higgins` | 5 | |
| | `daturkel-landmark-ml-papers` | 74 | |
| | `dblp-xml-snapshot` | 378818 | |
| | `epoch-all-ai-models` | 1726 | |
| | `europe-pmc` | 49201 | |
| | `gh-ml-hf-daily-papers` | 4 | |
| | `gh-ml-repository-doi-refs` | 14 | |
| | `hf-ml-doi-snapshot` | 1 | |
| | `hf-ml-snapshot` | 9 | |
| | `icml-test-of-time` | 9 | |
| | `medrxiv` | 390 | |
| | `neurips-test-of-time` | 3 | |
| | `openalex-snapshot-crossfield-ml` | 19696 | |
| | `openalex-snapshot-cs` | 344805 | |
| | `openalex-works` | 593 | |
| | `pubmed-bulk` | 5 | |
| | `spdin-deep-learning-chronology` | 55 | |
|
|
| | Record type | Rows | |
| | --- | ---: | |
| | `blog` | 152 | |
| | `cited_document` | 1168 | |
| | `model_card` | 248 | |
| | `paper` | 1531068 | |
| | `technical_report` | 214 | |
|
|
| | Metadata status | Rows | |
| | --- | ---: | |
| | (not reported) | — | |
|
|
|
|
|
|
| Chronology and coverage are recorded by the run manifest: |
|
|
| | (not reported) | — | |
|
|
| ## Row schema |
|
|
| Rows preserve title, abstract, DOI or arXiv URL, source, source revision, |
| source license, article license, group identity, exact text hash, model score, |
| model inclusion, final inclusion, inclusion reason, classifier or curated |
| reference provenance, text basis, language, and eligibility status. Each row |
| also has `record_type` (`paper`, `technical_report`, `model_card`, |
| `announcement/blog`, or `cited_document`) and `metadata_status` |
| (`corpus_metadata`, `corpus_matched`, `hydrated`, `citation_only`, or |
| `unavailable`). Text basis is one of `title_abstract`, `title_only`, |
| `abstract_only`, or `no_text`. |
|
|
| This is a broad ML-research dataset, not a claim that every primary record is |
| a conventional paper. Curated direct-document references remain typed even |
| when they have no DOI, using a stable source URL key and metadata-availability |
| flags. A missing document URL remains an audit configuration such as |
| `no_document_reference`; it does not create a guessed paper. |
| An explicit citation without a URL can still retain its `reference_label`, |
| title, authors, year, stable source key, and metadata-availability flag. |
|
|
| Curated references are post-hoc additions retained only after an explicit |
| curator source audit. A curated override is provenance, not evidence that the |
| classifier has 100% recall. Rows with `inclusion_reason=curated_reference` |
| make that override explicit. Curated scholarly references from Epoch and picked |
| chronologies are retained irrespective of the classifier decision. |
|
|
| The high-recall policy is `high_recall_with_review_v1`: scorer threshold `0.35`, primary/default inclusion threshold `0.5`, and every scorer-positive row is retained in the audit collection. Curated references override the score. Non-curated rows in the `[0.35, 0.5)` band are retained in the optional `review_candidates` config with `included=false`, `inclusion_reason=review_candidate`, and review flags. Language and title-only uncertainty are flags, not vetoes. This review is not a population statistic or an accuracy estimate. |
|
|
| ## Classifier provenance |
|
|
| | Field | Value | |
| | --- | --- | |
| | `rubric_version` | ml-methods-neural-apps-v1 | |
| | `model_version` | paper-ml-tfidf-logreg-v1 | |
| | `model_sha256` | df506fb1480a729f827f9825714b330a251499a07cdb1d223c5405095ac5e8a0 | |
| | `threshold` | 0.35 | |
| | `language_policy` | English normlangid confidence >= 0.90 is a review flag after model scoring; it does not veto model-positive inclusion | |
| | `provenance.evaluation_counts` | 79 | |
| | `provenance.language_detector` | langid-1.1.6-normalized | |
| | `provenance.training_counts` | 320 | |
| | `provenance.training_fingerprint` | 0d050304377d4727ccf627947c7bc33b76f66710ae6b6852521000864599554c | |
|
|
| | Release metadata | Value | |
| | --- | --- | |
| | `dataset_scope` | broad_ml_research_v1 | |
| | `inclusion_policy` | high_recall_with_review_v1 | |
|
|
| The current classifier was trained with 320 assistant-origin training |
| annotations and evaluated on 79 assistant-origin evaluation annotations under |
| the earlier scope. It remains a coverage anchor for blind spots; it does not |
| define the recall-first inclusion policy. Those metrics are agreement checks and |
| are not validated accuracy, human gold evaluation, or a population estimate. |
| Title-only and language-uncertain rows are retained with flags. |
|
|
| ## Licensing and reproducibility |
|
|
| Source-specific licenses are preserved per row. This card assigns no global |
| redistribution license, and the release contains paper metadata/abstract |
| fields rather than paper full text. Keep the immutable manifest, captured |
| high-water mark, source revisions, model checksum, chunk receipts, and any |
| curation audit together when reproducing the run. |
|
|
| Files declared by the manifest: |
|
|
| - `README.md` |
| - `coverage/references.parquet` |
| - `coverage/summary.json` |
| - `data/part-00000.parquet` |
| - `data/part-00001.parquet` |
| - `data/part-00002.parquet` |
| - `data/part-00003.parquet` |
| - `data/part-00004.parquet` |
| - `data/part-00005.parquet` |
| - `data/part-00006.parquet` |
| - `data/part-00007.parquet` |
| - `data/part-00008.parquet` |
| - `data/part-00009.parquet` |
| - `data/part-00010.parquet` |
| - `data/part-00011.parquet` |
| - `data/part-00012.parquet` |
| - `data/part-00013.parquet` |
| - `data/part-00014.parquet` |
| - `data/part-00015.parquet` |
| - `data/part-00016.parquet` |
| - `data/part-00017.parquet` |
| - `data/part-00018.parquet` |
| - `data/part-00019.parquet` |
| - `data/part-00020.parquet` |
| - `data/part-00021.parquet` |
| - `data/part-00022.parquet` |
| - `data/part-00023.parquet` |
| - `data/part-00024.parquet` |
| - `data/part-00025.parquet` |
| - `data/part-00026.parquet` |
| - `data/part-00027.parquet` |
| - `data/part-00028.parquet` |
| - `data/part-00029.parquet` |
| - `data/part-00030.parquet` |
| - `data/part-00031.parquet` |
| - `data/part-00032.parquet` |
| - `data/part-00033.parquet` |
| - `data/part-00034.parquet` |
| - `data/part-00035.parquet` |
| - `data/part-00036.parquet` |
| - `data/part-00037.parquet` |
| - `data/part-00038.parquet` |
| - `data/part-00039.parquet` |
| - `data/part-00040.parquet` |
| - `data/part-00041.parquet` |
| - `data/part-00042.parquet` |
| - `data/part-00043.parquet` |
| - `data/part-00044.parquet` |
| - `data/part-00045.parquet` |
| - `data/part-00046.parquet` |
| - `provenance/model-manifest.json` |
| - `provenance/source-manifest.json` |
| - `review/data/part-00000.parquet` |
| - `review/data/part-00001.parquet` |
| - `review/data/part-00002.parquet` |
| - `review/data/part-00003.parquet` |
| - `review/data/part-00004.parquet` |
| - `review/data/part-00005.parquet` |
| - `review/data/part-00006.parquet` |
| - `review/data/part-00007.parquet` |
| - `review/data/part-00008.parquet` |
| - `review/data/part-00009.parquet` |
| - `review/data/part-00010.parquet` |
| - `review/data/part-00011.parquet` |
| - `review/data/part-00012.parquet` |
| - `review/data/part-00013.parquet` |
| - `review/data/part-00014.parquet` |
| - `review/data/part-00015.parquet` |
| - `review/data/part-00016.parquet` |
| - `review/data/part-00017.parquet` |
| - `review/data/part-00018.parquet` |
| - `review/data/part-00019.parquet` |
| - `review/data/part-00020.parquet` |
| - `review/data/part-00021.parquet` |
| - `review/data/part-00022.parquet` |
| - `review/data/part-00023.parquet` |
| - `review/data/part-00024.parquet` |
| - `review/data/part-00025.parquet` |
| - `review/data/part-00026.parquet` |
| - `review/data/part-00027.parquet` |
| - `review/data/part-00028.parquet` |
| - `review/data/part-00029.parquet` |
| - `review/data/part-00030.parquet` |
| - `review/data/part-00031.parquet` |
| - `review/data/part-00032.parquet` |
| - `review/data/part-00033.parquet` |
| - `review/data/part-00034.parquet` |
| - `review/data/part-00035.parquet` |
| - `review/data/part-00036.parquet` |
| - `review/data/part-00037.parquet` |
| - `review/data/part-00038.parquet` |
| - `review/data/part-00039.parquet` |
| - `review/data/part-00040.parquet` |
| - `review/data/part-00041.parquet` |
| - `review/data/part-00042.parquet` |
| - `review/data/part-00043.parquet` |
| - `review/data/part-00044.parquet` |
| - `review/data/part-00045.parquet` |
| - `review/data/part-00046.parquet` |
| - `review/data/part-00047.parquet` |
| - `review/data/part-00048.parquet` |
| - `review/data/part-00049.parquet` |
| - `review/data/part-00050.parquet` |
| - `review/data/part-00051.parquet` |
| - `review/data/part-00052.parquet` |
| - `review/data/part-00053.parquet` |
| - `review/data/part-00054.parquet` |
| - `review/data/part-00055.parquet` |
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| - `review/data/part-00057.parquet` |
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| - `review/data/part-00061.parquet` |
| - `review/data/part-00062.parquet` |
| - `review/data/part-00063.parquet` |
| - `review/data/part-00064.parquet` |
| - `review/data/part-00065.parquet` |
| - `review/data/part-00066.parquet` |
| - `review/data/part-00067.parquet` |
| - `review/data/part-00068.parquet` |
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| - `review/data/part-00110.parquet` |
| - `review/data/part-00111.parquet` |
| - `review/data/part-00112.parquet` |
| - `review/data/part-00113.parquet` |
| - `review/data/part-00114.parquet` |
| - `review/data/part-00115.parquet` |
| - `review/data/part-00116.parquet` |
| - `review/data/part-00117.parquet` |
| - `review/data/part-00118.parquet` |
| - `review/data/part-00119.parquet` |
| - `review/data/part-00120.parquet` |
| - `review/data/part-00121.parquet` |
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| - `review/data/part-00123.parquet` |
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| - `review/data/part-00165.parquet` |
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| - `review/data/part-00180.parquet` |
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| - `review/data/part-00182.parquet` |
| - `review/data/part-00183.parquet` |
| - `review/data/part-00184.parquet` |
| - `review/data/part-00185.parquet` |
| - `review/data/part-00186.parquet` |
| - `review/data/part-00187.parquet` |
| - `review/data/part-00188.parquet` |
| - `review/data/part-00189.parquet` |
| - `review/data/part-00190.parquet` |
|
|
