Result

Partial label accuracy of C2S (GPT-2 Large) on L1000

0.631 Partial label accuracy

Methods

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: Not reported scored / Not reported eligible
Uncertainty: ± 0.0031 (type not stated)
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

Split: Not reported
Adaptation: Not reported
Scoring implementation: Not reported

No execution recipe has been verified for this exact configuration and evaluation. A benchmark's general instructions may use different inputs, splits or model settings.

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

Source checking verifies the cited claim or transcription. It does not establish independent reproduction.

Evidence table

Inspect claims, sources and review details

Trace each statement to its source and review. A context-only reference supports the record generally; it does not verify an individual field. Source checking does not reproduce an experiment.

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1 evidence row matching the loaded filters

Claims, original sources and review scope · Release 2026-11-02-a7f03c9e55a5
Property and statement	Original source and location	Review and provenance
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 ["ai-assisted-source-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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Sources and history

Release 2026-11-02-a7f03c9e55a5 · Record review: source checked

1 source record and release history

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: type: unresolved_spread; printed: ± 0.0031; value: 0.0031
source locator: Table 3, Partial label / C2S (GPT-2 Large) row, L1000 Acc column
review: method: ai-assisted-source-review; reviewer: codex; reviewed at: 2026-09-16T10:41:16.533640+00:00; 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; method note: independent; table-level review; reviewer note: role: omics research agent; independent source-table review; not human review; note: 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.
legacy id: lit-027
missing metadata: dataset version: reason: unextracted; split: reason: unextracted

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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