Evidence claim

leakage_control: pheno-20261022-data-song2025-simple

Evidence concern: excluded from comparisons

Appendix A.2 describes the random baseline as predicting hit with probability equal to 'the overall proportion of actual hits in the specific benchmark dataset'. With one pooled rate (485 of 1,175 = 41.3%, Table 3) the expected PPV, sensitivity, F1 and FPR are all about 0.41 and specificity and NPV about 0.59. Table 8 prints PPV 0.47, sensitivity 0.46, F1 0.47, FPR 0.36, specificity 0.64 and NPV 0.63. With each screen's own hit rate (Table 3) the expected values are 0.47, 0.47, 0.47, 0.37, 0.63 and 0.63, which match. One draw at the pooled rate would need sensitivity about 2 standard errors above and FPR about 3 below expectation at once. The baseline therefore probably uses per-screen hit rates, which is information a screen designer would not have before the screen. The expected values were computed by the reviewer from Table 3 counts and are not stored as results. Treat the random row as a per-screen-prevalence classifier, not a matched random-selection comparator.Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? · Appendix A.2; Table 3; Table 1, row "Random Baseline"; Table 8, row "Random N/A N/A"

Leakage control of Virtual CRISPR Simple Benchmark

The Simple Benchmark's four screens come from BioGRID-ORCS v1.1.16, the database the embedding classifier is also trained on (the training release is not stated); the authors evaluate the classifier only on the Difficult Benchmark 'to mitigate potential bias from dataset similarity'. Only prompted LLMs are scored on the Simple Benchmark.

Descriptive fact transcribed from the pinned source.

Evidence

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Evidence table

Inspect claims, sources and review details

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6 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-10-23-5347695500ed
Property and statement	Original source and location	Review and provenance
Claimed field leakage_control Context-only references	Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Original source ↗ Section 2.3 'Simple Benchmark'; Section 3 Version: Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP 2025), pages 354-364, 1 August 2025; ACL Anthology 2025.bionlp-1.30 Retrieved: 2026-10-22T13:57:26Z	not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.field` Source artifact SHA-256: `6c53ffec88444768fbb5c1a65031c096f07b3d9ac48de8163bc8f47d0d51205c` Hash scope: pdftotext -layout text layer, parsed by data/omics/use-case-refresh-phenotype-20261022/extract/song2025virtualcrispr.py with row labels asserted Inspected artifact
Source location Section 2.3 'Simple Benchmark'; Section 3 Context-only references	Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Original source ↗ Section 2.3 'Simple Benchmark'; Section 3 Version: Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP 2025), pages 354-364, 1 August 2025; ACL Anthology 2025.bionlp-1.30 Retrieved: 2026-10-22T13:57:26Z	not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.source_locator` Source artifact SHA-256: `6c53ffec88444768fbb5c1a65031c096f07b3d9ac48de8163bc8f47d0d51205c` Hash scope: pdftotext -layout text layer, parsed by data/omics/use-case-refresh-phenotype-20261022/extract/song2025virtualcrispr.py with row labels asserted Inspected artifact
Claimed value The Simple Benchmark's four screens come from BioGRID-ORCS v1.1.16, the database the embedding classifier is also trained on (the training release is not stated); the authors evaluate the classifier only on the Difficult Benchmark 'to mitigate potential bias from dataset similarity'. Only prompted LLMs are scored on the Simple Benchmark. Context-only references	Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Original source ↗ Section 2.3 'Simple Benchmark'; Section 3 Version: Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP 2025), pages 354-364, 1 August 2025; ACL Anthology 2025.bionlp-1.30 Retrieved: 2026-10-22T13:57:26Z	not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `attributes.value` Source artifact SHA-256: `6c53ffec88444768fbb5c1a65031c096f07b3d9ac48de8163bc8f47d0d51205c` Hash scope: pdftotext -layout text layer, parsed by data/omics/use-case-refresh-phenotype-20261022/extract/song2025virtualcrispr.py with row labels asserted Inspected artifact
Description Descriptive fact transcribed from the pinned source. Context-only references	Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Original source ↗ Section 2.3 'Simple Benchmark'; Section 3 Version: Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP 2025), pages 354-364, 1 August 2025; ACL Anthology 2025.bionlp-1.30 Retrieved: 2026-10-22T13:57:26Z	not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `description` Source artifact SHA-256: `6c53ffec88444768fbb5c1a65031c096f07b3d9ac48de8163bc8f47d0d51205c` Hash scope: pdftotext -layout text layer, parsed by data/omics/use-case-refresh-phenotype-20261022/extract/song2025virtualcrispr.py with row labels asserted Inspected artifact
Relationship: subject pheno-20261022-data-song2025-simple Context-only references	Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Original source ↗ Section 2.3 'Simple Benchmark'; Section 3 Version: Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP 2025), pages 354-364, 1 August 2025; ACL Anthology 2025.bionlp-1.30 Retrieved: 2026-10-22T13:57:26Z	not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `links:subject:pheno-20261022-data-song2025-simple` Source artifact SHA-256: `6c53ffec88444768fbb5c1a65031c096f07b3d9ac48de8163bc8f47d0d51205c` Hash scope: pdftotext -layout text layer, parsed by data/omics/use-case-refresh-phenotype-20261022/extract/song2025virtualcrispr.py with row labels asserted Inspected artifact
Name leakage_control: pheno-20261022-data-song2025-simple Context-only references	Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? Original source ↗ Section 2.3 'Simple Benchmark'; Section 3 Version: Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP 2025), pages 354-364, 1 August 2025; ACL Anthology 2025.bionlp-1.30 Retrieved: 2026-10-22T13:57:26Z	not individually reviewed No individual claim review recorded Source has a recorded evidence concern. Consult its source page before using the claim. Audit details Field: `name` Source artifact SHA-256: `6c53ffec88444768fbb5c1a65031c096f07b3d9ac48de8163bc8f47d0d51205c` Hash scope: pdftotext -layout text layer, parsed by data/omics/use-case-refresh-phenotype-20261022/extract/song2025virtualcrispr.py with row labels asserted Inspected artifact

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Sources and history

Release 2026-10-23-5347695500ed · Record review: source checked

1 source record and release history

Virtual CRISPR: Can LLMs Predict CRISPR Screen Results? · Original source · Proceedings of the 24th Workshop on Biomedical Language Processing (BioNLP 2025), pages 354-364, 1 August 2025; ACL Anthology 2025.bionlp-1.30

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Technical metadata and extraction receipts

Stable ID: pheno-20261022-claim-song2025-simple-from-orcs

field: leakage_control
value: The Simple Benchmark's four screens come from BioGRID-ORCS v1.1.16, the database the embedding classifier is also trained on (the training release is not stated); the authors evaluate the classifier only on the Difficult Benchmark 'to mitigate potential bias from dataset similarity'. Only prompted LLMs are scored on the Simple Benchmark.
source locator: Section 2.3 'Simple Benchmark'; Section 3
review: method: source-hash-verification; ai-assisted-source-review; method note: Read the cited sections of the pinned PDF text layer and checked the claim's wording against them.; reviewer: claude; reviewer note: Claude (Opus 5.5) review agent, independent of the extractor; no human review claimed; date: 2026-10-22; artifact sha256: 6c53ffec88444768fbb5c1a65031c096f07b3d9ac48de8163bc8f47d0d51205c; retrieval url: https://aclanthology.org/2025.bionlp-1.30.pdf; note: Reviewer reworded: the training release is not stated, and the authors' reason is quoted from Section 3.

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subject: Virtual CRISPR Simple Benchmark

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