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1 evaluation · 2 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Random selection (Roohani et al. 2025) | Protocol: BioDiscoveryAgent 1-gene perturbation design: hit ratio after 5 rounds of 128 genes Dataset: CAR-T proliferation screen (unpublished dataset used by Roohani et al. 2025) | 0.033 recall fraction · higher Uncertainty: Not yet extracted: Appendix Table 7 prints one standard deviation over 10 runs for these values; not extracted in this pass. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRandom on CAR-T (Roohani et al. 2025) tgtval-20261009-protocol-roohani2025-hitratio-round5 Aggregation: Not reported BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments · Table 1, row 'Random', column 'All' under 'CAR-T' |
| Configuration: Random selection (Roohani et al. 2025) | Protocol: BioDiscoveryAgent 1-gene perturbation design: hit ratio after 5 rounds of 128 genes Dataset: CAR-T proliferation screen (unpublished dataset used by Roohani et al. 2025) | 0.02 recall fraction · higher Uncertainty: Not yet extracted: Appendix Table 7 prints one standard deviation over 10 runs for these values; not extracted in this pass. Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceRandom on CAR-T (Roohani et al. 2025) tgtval-20261009-protocol-roohani2025-hitratio-round5 Aggregation: Not reported BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments · Table 1, row 'Random', column 'N/E' under 'CAR-T' |
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tgtval-20261009-protocol-roohani2025-hitratio-round5
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19 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| attributes.comparison.adaptation Selection only; no model fitting for the agent rows Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.aggregation Mean over 10 runs Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.budget 5 rounds x 128 genes Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.dataset_version Offline replay of the screen Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.inputs Phenotype description and the responses revealed in previous rounds Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.metric_implementation Not reported Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | missing or unspecified No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.population Genes assayed by the CAR-T screen Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.protocol_id tgtval-20261009-protocol-roohani2025-hitratio-round5 Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
| attributes.comparison.split No training split; 5 sequential selection rounds Context-only references | BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
attributes.limitations1 values
| BioDiscoveryAgent: An AI Agent for Designing Genetic Perturbation Experiments Table 1, row 'Random', columns for 'CAR-T' Version: arXiv:2405.17631 version 3, updated 2025-03-09; published as a conference paper at ICLR 2025 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: pdftotext -layout text layer, parsed by extract/extract_target_validation.py |
Release 2026-10-10-6e93f504adfc · Record review: source checked
Stable ID: tgtval-20261009-eval-roohani2025-random-cart-proliferation