The split of Srivatsan20 that PerturBench evaluated on. The upstream dataset release is not catalogued here, so no claim is made that this matches its original splits.
These checks assess whether the evidence supports a reproducible investigation. A source-checked score alone does not meet these requirements.
Release 2026-09-29-06401fd5b220 · Evidence verified: Not verified
Exact outcomes, predictions, identifiers and evaluator are connected.
Missing or unresolved evidence
Verified: Not verified
Replay evidence includes annotations and an assessment of dependence. Unknown independence permits descriptive analysis only.
Missing or unresolved evidence
Verified: Not verified
A pinned recipe describes the inputs, environment and resource requirements.
Missing or unresolved evidence
Verified: Not verified
Separate data and exposure records support an independent test.
Missing or unresolved evidence
Verified: Not verified
Readiness describes the evidence in this release. Availability on your computer is checked separately when an investigation runs. Existing data exposure can prevent independent validation even when files are available.
No verified artifact manifest is connected to this record yet. The gaps above identify what is needed before analysis can begin.
40 evaluations · 40 results. Different protocols are not a single leaderboard.
Applied filters: All linked evaluations
| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Biolord* | Task: PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Dataset subset: Srivatsan20 (PerturBench split) | 0.18 ± 1 × 10 − 1 cosine_logfc fraction · higher Uncertainty: type: standard_deviation; value: 0.1 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceTrain on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Biolord ∗), column(Cosine, log fold change (LogFC)) |
| Configuration: Biolord* | Task: PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Dataset subset: Srivatsan20 (PerturBench split) | 0.37 ± 2 × 10 − 2 cosine_logfc_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.02 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceBiolord* on PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Biolord ∗), column(Cosine, LogFC rank) |
| Configuration: Biolord* | Task: PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Dataset subset: Srivatsan20 (PerturBench split) | 0.35 ± 1 × 10 − 1 rmse_mean_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.1 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceBiolord* on PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Biolord ∗), column(RMSE, mean rank) |
| Configuration: Biolord* | Task: PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Dataset subset: Srivatsan20 (PerturBench split) | 0.086 ± 4 × 10 − 2 rmse_mean error · lower Uncertainty: type: standard_deviation; value: 0.04 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceBiolord* on PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Biolord ∗), column(RMSE, mean) |
| Configuration: CPA* | Task: PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Dataset subset: Srivatsan20 (PerturBench split) | 0.31 ± 1 × 10 − 2 cosine_logfc fraction · higher Uncertainty: type: standard_deviation; value: 0.01 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceTrain on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗), column(Cosine, log fold change (LogFC)) |
| Configuration: CPA* | Task: PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Dataset subset: Srivatsan20 (PerturBench split) | 0.35 ± 6 × 10 − 3 cosine_logfc_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.006 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* on PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗), column(Cosine, LogFC rank) |
| Configuration: CPA* | Task: PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Dataset subset: Srivatsan20 (PerturBench split) | 0.32 ± 7 × 10 − 3 rmse_mean_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.007 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* on PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗), column(RMSE, mean rank) |
| Configuration: CPA* | Task: PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Dataset subset: Srivatsan20 (PerturBench split) | 0.021 ± 4 × 10 − 4 rmse_mean error · lower Uncertainty: type: standard_deviation; value: 0.0004 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* on PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗), column(RMSE, mean) |
| Configuration: CPA* (noAdv) | Task: PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Dataset subset: Srivatsan20 (PerturBench split) | 0.37 ± 4 × 10 − 2 cosine_logfc fraction · higher Uncertainty: type: standard_deviation; value: 0.04 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceTrain on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (noAdv)), column(Cosine, log fold change (LogFC)) |
| Configuration: CPA* (noAdv) | Task: PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Dataset subset: Srivatsan20 (PerturBench split) | 0.33 ± 3 × 10 − 2 cosine_logfc_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.03 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* (noAdv) on PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (noAdv)), column(Cosine, LogFC rank) |
| Configuration: CPA* (noAdv) | Task: PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Dataset subset: Srivatsan20 (PerturBench split) | 0.29 ± 7 × 10 − 3 rmse_mean_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.007 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* (noAdv) on PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (noAdv)), column(RMSE, mean rank) |
| Configuration: CPA* (noAdv) | Task: PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Dataset subset: Srivatsan20 (PerturBench split) | 0.020 ± 8 × 10 − 4 rmse_mean error · lower Uncertainty: type: standard_deviation; value: 0.0008 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* (noAdv) on PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (noAdv)), column(RMSE, mean) |
| Configuration: CPA* (scGPT) | Task: PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Dataset subset: Srivatsan20 (PerturBench split) | 0.29 ± 9 × 10 − 4 cosine_logfc fraction · higher Uncertainty: type: standard_deviation; value: 0.0009 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceTrain on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (scGPT)), column(Cosine, log fold change (LogFC)) |
| Configuration: CPA* (scGPT) | Task: PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Dataset subset: Srivatsan20 (PerturBench split) | 0.38 ± 2 × 10 − 2 cosine_logfc_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.02 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* (scGPT) on PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (scGPT)), column(Cosine, LogFC rank) |
| Configuration: CPA* (scGPT) | Task: PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Dataset subset: Srivatsan20 (PerturBench split) | 0.32 ± 1 × 10 − 2 rmse_mean_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.01 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* (scGPT) on PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (scGPT)), column(RMSE, mean rank) |
| Configuration: CPA* (scGPT) | Task: PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Dataset subset: Srivatsan20 (PerturBench split) | 0.021 ± 3 × 10 − 4 rmse_mean error · lower Uncertainty: type: standard_deviation; value: 0.0003 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceCPA* (scGPT) on PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(CPA ∗ (scGPT)), column(RMSE, mean) |
| Configuration: Decoder (Cov) | Task: PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Dataset subset: Srivatsan20 (PerturBench split) | 0.30 ± 1 × 10 − 2 cosine_logfc fraction · higher Uncertainty: type: standard_deviation; value: 0.01 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceTrain on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder (Cov)), column(Cosine, log fold change (LogFC)) |
| Configuration: Decoder (Cov) | Task: PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Dataset subset: Srivatsan20 (PerturBench split) | 0.47 ± 9 × 10 − 3 cosine_logfc_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.009 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDecoder (Cov) on PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder (Cov)), column(Cosine, LogFC rank) |
| Configuration: Decoder (Cov) | Task: PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Dataset subset: Srivatsan20 (PerturBench split) | 0.50 ± 4 × 10 − 2 rmse_mean_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.04 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDecoder (Cov) on PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder (Cov)), column(RMSE, mean rank) |
| Configuration: Decoder (Cov) | Task: PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Dataset subset: Srivatsan20 (PerturBench split) | 0.023 ± 3 × 10 − 5 rmse_mean error · lower Uncertainty: type: standard_deviation; value: 0.00003 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDecoder (Cov) on PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder (Cov)), column(RMSE, mean) |
| Configuration: Decoder | Task: PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Dataset subset: Srivatsan20 (PerturBench split) | 0.35 ± 5 × 10 − 3 cosine_logfc fraction · higher Uncertainty: type: standard_deviation; value: 0.005 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceTrain on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder), column(Cosine, log fold change (LogFC)) |
| Configuration: Decoder | Task: PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Dataset subset: Srivatsan20 (PerturBench split) | 0.16 ± 1 × 10 − 2 cosine_logfc_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.01 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDecoder on PerturBench CT-COSINE-RANK: covariate transfer on Srivatsan20, Cosine LogFC rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder), column(Cosine, LogFC rank) |
| Configuration: Decoder | Task: PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Dataset subset: Srivatsan20 (PerturBench split) | 0.14 ± 7 × 10 − 3 rmse_mean_rank fraction · lower Uncertainty: type: standard_deviation; value: 0.007 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDecoder on PerturBench CT-RMSE-RANK: covariate transfer on Srivatsan20, RMSE mean rank Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder), column(RMSE, mean rank) |
| Configuration: Decoder | Task: PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Dataset subset: Srivatsan20 (PerturBench split) | 0.018 ± 1 × 10 − 4 rmse_mean error · lower Uncertainty: type: standard_deviation; value: 0.0001 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceDecoder on PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(Decoder), column(RMSE, mean) |
| Configuration: LA | Task: PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Dataset subset: Srivatsan20 (PerturBench split) | 0.45 ± 2 × 10 − 3 cosine_logfc fraction · higher Uncertainty: type: standard_deviation; value: 0.002 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceLA on PerturBench CT-COSINE: covariate transfer on Srivatsan20, Cosine similarity of log fold change Train on some cell types and predict drug effects in a held-out cell type, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, row(LA), column(Cosine, log fold change (LogFC)) |
Source checking is not independent reproduction. Release 2026-09-29-06401fd5b220.
This record describes a particular subset or cohort used in an evaluation. Its results do not describe the full dataset.
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
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.
2 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| description The split of Srivatsan20 that PerturBench evaluated on. The upstream dataset release is not catalogued here, so no claim is made that this matches its original splits. Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis No field-specific location recorded Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| name Srivatsan20 (PerturBench split) Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis No field-specific location recorded Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
View linked audit checks and correction history
Release 2026-09-29-06401fd5b220 · Record review: source checked
Stable ID: perturbench-dataset-srivatsan20