Result

0.631 Partial-label accuracy

C2S (GPT-2 Large) · Partial-label accuracy · L1000

Tested configuration: C2S (GPT-2 Large)
Task: Combinatorial cell-label classification
Dataset: L1000
Procedure: Partial-credit labels including cell type, perturbation, and dose.
Evaluation: C2S (GPT-2 Large): Combinatorial cell-label classification
Coverage: scored: unreported; eligible: unreported
Uncertainty: ± 0.0031
Evidence: Author-reported evaluation · source checkedCell2Sentence: Teaching Large Language Models the Language of Biology · Table 3, Partial label / C2S (GPT-2 Large) row, L1000 Acc column

A source-checked result verifies the numerical transcription, not every model or protocol detail. Evaluation metadata: needs review. Source checked does not mean independently reproduced.

Reproduction

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Adaptation: Not reported
Scoring implementation: Not reported

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Access requirements and official instructions: Combinatorial cell-label classification

Reproducing this published result requires matching its model configuration, data, split and scorer. Source checking or a successful smoke test does not establish score reproduction.

Evidence

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1 evidence row matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
Property and statement	Original source and location	Review and provenance
attributes.printed_value 0.631 Individual claims	Cell2Sentence: Teaching Large Language Models the Language of Biology Original source ↗ Table 3, Partial label / C2S (GPT-2 Large) row, L1000 Acc column Version: preprint archived 2024-10-29 Retrieved: 2026-09-16T10:41:16.533640+00:00	source checked independent ai table review · 2026-09-16T10:41:16.533640+00:00 author reported Audit details Read inline small-caps/bold XML in document order, restoring Geneformer and GPT-2 Large labels. Selected Partial label (first block), L1000 > Acc, not AUROC or Full label. This verifies the central score at its source location, not every metadata field or an experimental reproduction. Field: `attributes.printed_value` Claim: claim-lit-027 Source artifact SHA-256: `e088727d6e04857fccb7033a9b074e1850f775e86e7d2e99e603dde09558ab02` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact Extraction artifact SHA-256: `e088727d6e04857fccb7033a9b074e1850f775e86e7d2e99e603dde09558ab02` Extraction artifact

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Release 2026-09-29-06401fd5b220 · Record review: source checked

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Cell2Sentence: Teaching Large Language Models the Language of Biology · Original source · preprint archived 2024-10-29

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Technical metadata and extraction receipts

Stable ID: lit-027

areas: cells-tissues
tasks: Combinatorial cell-label classification
printed value: 0.631
numeric value: 0.631
metric: Partial-label accuracy
metric direction: unknown
unit: unitless
uncertainty: ± 0.0031
source locator: Table 3, Partial label / C2S (GPT-2 Large) row, L1000 Acc column
review: method: independent_ai_table_review; reviewer: Codex omics research agent; independent source-table review, not human review; reviewed at: 2026-09-16T10:41:16.533640+00:00; notes: Read inline small-caps/bold XML in document order, restoring Geneformer and GPT-2 Large labels. Selected Partial label (first block), L1000 > Acc, not AUROC or Full label. This verifies the central score at its source location, not every metadata field or an experimental reproduction.; evidence: {"table_xml_id": "T3", "row_cells": ["C2S (GPT-2 Large)", "0.639 ± 0.0049", "0.767 ± 0.0049", "0.631 ± 0.0031", "0.768 ± 0.0021", "0.575 ± 0.0035", "0.713 ± 0.0014"], "selected_cell_zero_based": 3, "selected_cell_xml": "<td align=\"center\" valign=\"middle\" rowspan=\"1\" colspan=\"1\"><bold>0.631</bold> ± <bold>0.0031</bold></td>", "caption": "Experimental results on downstream cell label classification. Cell labels are composed of multiple combinatorial metadata parts, including cell type, perturbations, and dosage information. Accuracy and area under ROC curve is computed on model predictions versus ground truth combinatorial labels, with partial credit given for partial misclassifications."}; artifact sha256: e088727d6e04857fccb7033a9b074e1850f775e86e7d2e99e603dde09558ab02; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11565894/fullTextXML
legacy id: lit-027
legacy row: id: lit-027; paper id: cell2sentence-2024; domain id: cells-tissues; task: Combinatorial cell-label classification; model: C2S (GPT-2 Large); model version: GPT-2 Large; dataset: L1000; dataset version: Not reported; split: Not reported; metric: Partial-label accuracy; value: 0.631; unit: unitless; uncertainty: ± 0.0031; protocol: Partial-credit labels including cell type, perturbation, and dose.; source locator: Table 3, Partial label / C2S (GPT-2 Large) row, L1000 Acc column; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC11565894/; evaluation origin: author_reported; reviewed utc: 2026-09-15T23:25:00Z
missing metadata: dataset version: not_reported_in_legacy_extract; split: not_reported_in_legacy_extract

Related records

evaluation: C2S (GPT-2 Large): Combinatorial cell-label classification
subject: Reported Partial-label accuracy for C2S (GPT-2 Large)

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