The 9 drug discovery tasks of BioML-bench v0.1-alpha, as listed in Table 3: polaris-pkis2-egfr-wt-c-1, polaris-adme-fang-hclint-1, polaris-adme-fang-hppb-1, polaris-adme-fang-solu-1, tdcommons-cyp2d6-substrate, tdcommons-lipophilicity, tdcommons-herg, tdcommons-bbb-martins, tdcommons-caco2-wang.
10 evaluations · 34 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: AIDE v6.3.3, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 30.6 ± 13.3% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 13.3 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAIDE on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'AIDE', column 'Above Median (%)' |
| Configuration: AIDE v6.3.3, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 7.4 ± 7.4% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 7.4 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAIDE on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'AIDE', column 'Any Medal (%)' |
| Configuration: AIDE v6.3.3, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 31.06 ± 8.88% Leaderboard percentile (mean over tasks in the domain; non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 8.88 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAIDE on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'AIDE', column 'Leaderboard Percentile' |
| Configuration: Biomni v0.0.5, Claude Sonnet 4 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 30.6 ± 12.3% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 12.3 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceBiomni on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'Biomni', column 'Above Median (%)' |
| Configuration: Biomni v0.0.5, Claude Sonnet 4 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 13.9 ± 11.1% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 11.1 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceBiomni on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'Biomni', column 'Any Medal (%)' |
| Configuration: Biomni v0.0.5, Claude Sonnet 4 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 32.55 ± 8.61% Leaderboard percentile (mean over tasks in the domain; non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 8.61 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceBiomni on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'Biomni', column 'Leaderboard Percentile' |
| Configuration: Dummy agent (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 0.0 ± 0.0% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 0.0 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDummy on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'Dummy', column 'Above Median (%)' |
| Configuration: Dummy agent (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 0.0 ± 0.0% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 0.0 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDummy on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'Dummy', column 'Any Medal (%)' |
| Configuration: Dummy agent (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 1.11 ± 1.11% Leaderboard percentile (mean over tasks in the domain; non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 1.11 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDummy on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'Dummy', column 'Leaderboard Percentile' |
| Configuration: MLAgentBench, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 16.7 ± 9.3% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 9.3 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMLAgentBench on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'MLAgentBench', column 'Above Median (%)' |
| Configuration: MLAgentBench, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 5.6 ± 3.7% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 3.7 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMLAgentBench on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'MLAgentBench', column 'Any Medal (%)' |
| Configuration: MLAgentBench, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 22.45 ± 5.93% Leaderboard percentile (mean over tasks in the domain; non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 5.93 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceMLAgentBench on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'MLAgentBench', column 'Leaderboard Percentile' |
| Configuration: STELLA, OpenRouter default backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 25.0 ± 11.0% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 11.0 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceSTELLA on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'STELLA', column 'Above Median (%)' |
| Configuration: STELLA, OpenRouter default backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 13.9 ± 7.3% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 7.3 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceSTELLA on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'STELLA', column 'Any Medal (%)' |
| Configuration: STELLA, OpenRouter default backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 28.84 ± 7.84% Leaderboard percentile (mean over tasks in the domain; non-penalized: runs without a valid submission omitted) percent · higher Uncertainty: ± 7.84 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceSTELLA on BioML-bench drug discovery (non-penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Non-penalized', domain 'Drug Discovery', row 'STELLA', column 'Leaderboard Percentile' |
| Configuration: AIDE v6.3.3, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 25.0 ± 11.0% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 11.0 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAIDE on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'AIDE', column 'Above Median (%)' |
| Configuration: AIDE v6.3.3, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 5.6 ± 5.6% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 5.6 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAIDE on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'AIDE', column 'Any Medal (%)' |
| Configuration: AIDE v6.3.3, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 80.6% Proportion (share of tasks that yield a valid, gradable submission (Section 3.4 definition); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAIDE on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'AIDE', column 'Completion Rate (%)' |
| Configuration: AIDE v6.3.3, GPT-4.1 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 24.75 ± 7.23% Leaderboard percentile (mean over tasks in the domain; penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 7.23 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceAIDE on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'AIDE', column 'Leaderboard Percentile' |
| Configuration: Biomni v0.0.5, Claude Sonnet 4 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 30.6 ± 12.3% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 12.3 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceBiomni on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'Biomni', column 'Above Median (%)' |
| Configuration: Biomni v0.0.5, Claude Sonnet 4 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 13.9 ± 11.1% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 11.1 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceBiomni on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'Biomni', column 'Any Medal (%)' |
| Configuration: Biomni v0.0.5, Claude Sonnet 4 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 100% Proportion (share of tasks that yield a valid, gradable submission (Section 3.4 definition); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceBiomni on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'Biomni', column 'Completion Rate (%)' |
| Configuration: Biomni v0.0.5, Claude Sonnet 4 backend (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 32.55 ± 8.61% Leaderboard percentile (mean over tasks in the domain; penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 8.61 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceBiomni on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'Biomni', column 'Leaderboard Percentile' |
| Configuration: Dummy agent (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 0.0 ± 0.0% Proportion (share of tasks where the agent's mean score exceeds the median human leaderboard submission (Section 3.4 definition); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 0.0 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDummy on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'Dummy', column 'Above Median (%)' |
| Configuration: Dummy agent (BioML-bench) | Protocol: BioML-bench drug discovery domain: agent leaderboard percentile over 9 tasks Dataset subset: BioML-bench v0.1-alpha drug discovery tasks (9 tasks) | 0.0 ± 0.0% Proportion (share of tasks where the agent reaches a public leaderboard medal threshold, MLE-bench definition (Section 3.4); penalized: runs without a valid submission scored as percentile 0) percent · higher Uncertainty: ± 0.0 (type not stated). Table 4 caption does not name the spread. Figures 2 and 4 show per-domain leaderboard percentiles as mean ± SEM across tasks; the Table 2 caption refers to the reported SEM. Coverage: Not reported scored / Not reported eligible | Independent external evaluation · Source checkedMethods, coverage and sourceDummy on BioML-bench drug discovery (penalized) lit-agents-20261013-biomlbench-protocol-drug-discovery Aggregation: Not reported BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML · Table 4 (page 12), block 'Penalized', domain 'Drug Discovery', row 'Dummy', column 'Any Medal (%)' |
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12 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Source location Table 3; repository experiments/biomlbench_v0.1a.txt Context-only references | BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: bioRxiv 2025.09.01.673319 version 3, posted 2025-09-28 (versions 1 and 2 posted 2025-09-04 and 2025-09-07) | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the PDF bytes as downloaded 2026-10-13T12:38:42Z. bioRxiv rewrites the XMP dates and document IDs, the Info ModDate and the trailer /ID on download, so a re-download does not reproduce the hash; the review found a fresh copy differing only in those 43 bytes, with an identical text layer. |
| Source location Table 3; repository experiments/biomlbench_v0.1a.txt Context-only references | science-machine/biomlbench repository at commit 673f3d8 Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Git commit 673f3d8d3462fc6cdcbbd9695fba612b9332ca65 (2025-09-14, head of main at retrieval); README title 'BioML-bench (v0.1-alpha)' | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the codeload tar.gz archive for the commit; two downloads gave identical bytes. Per-file hashes of the files cited are in sources.md. |
| Split Each task's train and test split as downloaded from its Polaris Hub benchmark Context-only references | BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: bioRxiv 2025.09.01.673319 version 3, posted 2025-09-28 (versions 1 and 2 posted 2025-09-04 and 2025-09-07) | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the PDF bytes as downloaded 2026-10-13T12:38:42Z. bioRxiv rewrites the XMP dates and document IDs, the Info ModDate and the trailer /ID on download, so a re-download does not reproduce the hash; the review found a fresh copy differing only in those 43 bytes, with an identical text layer. |
| Split Each task's train and test split as downloaded from its Polaris Hub benchmark Context-only references | science-machine/biomlbench repository at commit 673f3d8 Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Git commit 673f3d8d3462fc6cdcbbd9695fba612b9332ca65 (2025-09-14, head of main at retrieval); README title 'BioML-bench (v0.1-alpha)' | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the codeload tar.gz archive for the commit; two downloads gave identical bytes. Per-file hashes of the files cited are in sources.md. |
| Subset scope 9 tasks listed under 'Drug Discovery' in Table 3. Polaris Hub (paper Table 1). Five tasks are Polaris-hosted Therapeutics Data Commons (tdcommons) benchmarks; four are Polaris ADME (Fang et al.) and PKIS2 kinase benchmarks. Context-only references | BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: bioRxiv 2025.09.01.673319 version 3, posted 2025-09-28 (versions 1 and 2 posted 2025-09-04 and 2025-09-07) | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the PDF bytes as downloaded 2026-10-13T12:38:42Z. bioRxiv rewrites the XMP dates and document IDs, the Info ModDate and the trailer /ID on download, so a re-download does not reproduce the hash; the review found a fresh copy differing only in those 43 bytes, with an identical text layer. |
| Subset scope 9 tasks listed under 'Drug Discovery' in Table 3. Polaris Hub (paper Table 1). Five tasks are Polaris-hosted Therapeutics Data Commons (tdcommons) benchmarks; four are Polaris ADME (Fang et al.) and PKIS2 kinase benchmarks. Context-only references | science-machine/biomlbench repository at commit 673f3d8 Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Git commit 673f3d8d3462fc6cdcbbd9695fba612b9332ca65 (2025-09-14, head of main at retrieval); README title 'BioML-bench (v0.1-alpha)' | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the codeload tar.gz archive for the commit; two downloads gave identical bytes. Per-file hashes of the files cited are in sources.md. |
| Version BioML-bench v0.1-alpha task set (experiments/biomlbench_v0.1a.txt at commit 673f3d8) Context-only references | BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: bioRxiv 2025.09.01.673319 version 3, posted 2025-09-28 (versions 1 and 2 posted 2025-09-04 and 2025-09-07) | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the PDF bytes as downloaded 2026-10-13T12:38:42Z. bioRxiv rewrites the XMP dates and document IDs, the Info ModDate and the trailer /ID on download, so a re-download does not reproduce the hash; the review found a fresh copy differing only in those 43 bytes, with an identical text layer. |
| Version BioML-bench v0.1-alpha task set (experiments/biomlbench_v0.1a.txt at commit 673f3d8) Context-only references | science-machine/biomlbench repository at commit 673f3d8 Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Git commit 673f3d8d3462fc6cdcbbd9695fba612b9332ca65 (2025-09-14, head of main at retrieval); README title 'BioML-bench (v0.1-alpha)' | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the codeload tar.gz archive for the commit; two downloads gave identical bytes. Per-file hashes of the files cited are in sources.md. |
| Description The 9 drug discovery tasks of BioML-bench v0.1-alpha, as listed in Table 3: polaris-pkis2-egfr-wt-c-1, polaris-adme-fang-hclint-1, polaris-adme-fang-hppb-1, polaris-adme-fang-solu-1, tdcommons-cyp2d6-substrate, tdcommons-lipophilicity, tdcommons-herg, tdcommons-bbb-martins, tdcommons-caco2-wang. Context-only references | BioML-bench: Evaluation of AI Agents for End-to-End Biomedical ML Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: bioRxiv 2025.09.01.673319 version 3, posted 2025-09-28 (versions 1 and 2 posted 2025-09-04 and 2025-09-07) | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the PDF bytes as downloaded 2026-10-13T12:38:42Z. bioRxiv rewrites the XMP dates and document IDs, the Info ModDate and the trailer /ID on download, so a re-download does not reproduce the hash; the review found a fresh copy differing only in those 43 bytes, with an identical text layer. |
| Description The 9 drug discovery tasks of BioML-bench v0.1-alpha, as listed in Table 3: polaris-pkis2-egfr-wt-c-1, polaris-adme-fang-hclint-1, polaris-adme-fang-hppb-1, polaris-adme-fang-solu-1, tdcommons-cyp2d6-substrate, tdcommons-lipophilicity, tdcommons-herg, tdcommons-bbb-martins, tdcommons-caco2-wang. Context-only references | science-machine/biomlbench repository at commit 673f3d8 Table 3; repository experiments/biomlbench_v0.1a.txt Shared locator for this statement’s cited sources; not a separate locator for each citation. Version: Git commit 673f3d8d3462fc6cdcbbd9695fba612b9332ca65 (2025-09-14, head of main at retrieval); README title 'BioML-bench (v0.1-alpha)' | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: SHA-256 of the codeload tar.gz archive for the commit; two downloads gave identical bytes. Per-file hashes of the files cited are in sources.md. |
Release 2026-11-02-a7f03c9e55a5 · Record review: source checked
Stable ID: lit-agents-20261013-biomlbench-data-drug-discovery-tasks