PerturBench evaluation of LA (scGPT) on combination prediction on Norman19, Cosine similarity of log fold change, scored with Cosine similarity of log fold change.
1 evaluation · 1 result. Different protocols are not a single leaderboard.
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| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: LA (scGPT) | Task: PerturBench CB-COSINE: combination prediction on Norman19, Cosine similarity of log fold change Dataset subset: Norman19 (PerturBench split) | 0.77 ± 4 × 10 − 3 Perturbench cosine logfc fraction · higher Uncertainty: SD 0.004 Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourcePredict the effect of a pair of gene overexpressions from single perturbations, reported as the mean and one standard deviation over seeds. Aggregation: Not reported PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) |
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Predict the effect of a pair of gene overexpressions from single perturbations, reported as the mean and one standard deviation over seeds.
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10 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Comparison: metric implementation Cosine similarity of log fold change Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Comparison: protocol id perturbench-task-cb-cosine Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Origin author_reported Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Protocol Predict the effect of a pair of gene overexpressions from single perturbations, reported as the mean and one standard deviation over seeds. Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Source location Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Description PerturBench evaluation of LA (scGPT) on combination prediction on Norman19, Cosine similarity of log fold change, scored with Cosine similarity of log fold change. Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Relationship: assessment perturbench-task-cb-cosine Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Relationship: data perturbench-dataset-norman19 Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Relationship: system perturbench-method-la-scgpt Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
| Name LA (scGPT) on PerturBench CB-COSINE: combination prediction on Norman19, Cosine similarity of log fold change Context-only references | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(LA (scGPT)), column(Cosine, log fold change (LogFC)) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | not individually reviewed No individual claim review recorded author reported Audit detailsField: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. |
Release 2026-11-02-a7f03c9e55a5 · Record review: source checked
Stable ID: perturbench-evaluation-la-scgpt-cb-cosine