denominator: tgtval-20261009-protocol-gupta2025-cumulative-hits-round5
Descriptive fact transcribed from the pinned source.
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.
One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.
6 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.field denominator Context-only references | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? Tables 1, 2 and 3, row 'Ground truth (| Cgt |)' Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.source_locator Tables 1, 2 and 3, row 'Ground truth (| Cgt |)' Context-only references | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? Tables 1, 2 and 3, row 'Ground truth (| Cgt |)' Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.value Printed ground-truth hit counts |C_gt| per screen: IL2 654, IFNG 920, Carnevale 943, Sanchez 924, Sanchez Down 924. The same five values are printed in Tables 1, 2 and 3. Context-only references | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? Tables 1, 2 and 3, row 'Ground truth (| Cgt |)' Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| description Descriptive fact transcribed from the pinned source. Context-only references | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? Tables 1, 2 and 3, row 'Ground truth (| Cgt |)' Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| Relationship: subject tgtval-20261009-protocol-gupta2025-cumulative-hits-round5 Context-only references | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? Tables 1, 2 and 3, row 'Ground truth (| Cgt |)' Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| name denominator: tgtval-20261009-protocol-gupta2025-cumulative-hits-round5 Context-only references | LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? Tables 1, 2 and 3, row 'Ground truth (| Cgt |)' Version: Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
Sources and history
Release 2026-10-10-6e93f504adfc · Record review: source checked
1 source records and release history
- LLMs for Bayesian Optimization in Scientific Domains: Are We There Yet? · Original source · Findings of the Association for Computational Linguistics: EMNLP 2025, pages 15482-15510
Technical metadata and extraction receipts
Stable ID: tgtval-20261009-claim-gupta2025-ground-truth-hits
- field
- denominator
- value
- Printed ground-truth hit counts |C_gt| per screen: IL2 654, IFNG 920, Carnevale 943, Sanchez 924, Sanchez Down 924. The same five values are printed in Tables 1, 2 and 3.
- source locator
- Tables 1, 2 and 3, row 'Ground truth (| Cgt |)'
- review
- method: source-hash-verification; ai-assisted-source-review; reviewer: claude; reviewer note: Separate Claude review agent, independent of the extractor; no human review claimed; reviewed at: 2026-10-09T21:22:54Z; artifact sha256: 7dda0b590f2736b7d30e48b97167a0868a2b4bde253589d8aff7929d01506ff9; retrieval url: https://aclanthology.org/2025.findings-emnlp.838.pdf; note: Hand transcription from the source text. Independent review 2026-10-09: checked against the re-downloaded PDF text; see docs/reviews/use-cases/therapeutic-target-validation-2026-10-09.md.