0.016 ± 8 × 10 − 4 rmse_mean_rank
Linear · PerturBench CB-RMSE-RANK · RMSE mean rank
- Tested configuration
- Linear
- Task
- PerturBench CB-RMSE-RANK: combination prediction on Norman19, RMSE mean rank
- Dataset subset
- Norman19 (PerturBench split)
- Procedure
- Predict the effect of a pair of gene overexpressions from single perturbations, reported as the mean and one standard deviation over seeds.
- Evaluation
- Linear on PerturBench CB-RMSE-RANK: combination prediction on Norman19, RMSE mean rank
- Evidence
- Author-reported evaluation · source checkedPerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 3, row(Linear), column(RMSE, mean rank)
A source-checked result verifies the numerical transcription, not every model or protocol detail. Evaluation metadata: source checked. Source checked does not mean independently reproduced.
Methods and reproduction
PerturBench evaluation of Linear on combination prediction on Norman19, RMSE mean rank, scored with RMSE mean rank.
- task
- PerturBench CB-RMSE-RANK: combination prediction on Norman19, RMSE mean rank
- configuration
- Linear
- dataset subset
- Norman19 (PerturBench split)
- Split
- Not reported
- Adaptation
- Not reported
- Scoring implementation
- RMSE mean rank
No execution recipe has been verified for this exact configuration and evaluation. A benchmark's general instructions may use different inputs, splits or model settings.
Reproducing this published result requires matching its model configuration, data, split and scorer. Source checking or a successful smoke test does not establish score reproduction.
Evaluation results
Release 2026-09-17-134cd1815de8 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard. Where several source tables report the same metric, the published comparisons above offer a pooled view that names what it does not hold constant.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| Linear on PerturBench CB-RMSE-RANK: combination prediction on Norman19, RMSE mean rank Configuration: LinearTask: PerturBench CB-RMSE-RANK: combination prediction on Norman19, RMSE mean rankDataset subset: Norman19 (PerturBench split) Predict the effect of a pair of gene overexpressions from single perturbations, reported as the mean and one standard deviation over seeds. Author-reported evaluation · Evaluation metadata: source checked | ||
| 0.016 ± 8 × 10 − 4 rmse_mean_rank Unit: fraction · Direction: lower | Uncertainty: type: standard deviation; value: 0.0008 Scored: Not reported · Eligible: Not reported | source checkedPerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 3, row(Linear), column(RMSE, mean rank) Source checking is not 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.
1 evidence row matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Reported result 0.016 ± 8 × 10 − 4 Individual claims | PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis Table 3, row(Linear), column(RMSE, mean rank) Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256 | source checked Deterministic parse of the pinned HTML tables, with row and column counts asserted · 2026-09-18 author reported Audit detailsSource checked, not reproduced. Metrics differ by task, so no composite score across tasks is computed or implied. Field: Source artifact SHA-256: Hash scope: Exact retrieved primary paper artifact bytes. Extraction artifact SHA-256: |
Sources and history
Release 2026-09-17-134cd1815de8 · Record review: source checked
1 source records and release history
- PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Original source · Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256
Technical metadata and extraction receipts
Stable ID: perturbench-result-linear-cb-rmse-rank-rmse-mean-rank
- areas
- cells-tissues
- tasks
- combination prediction on Norman19, RMSE mean rank
- metric
- rmse_mean_rank
- metric direction
- lower
- unit
- fraction
- printed value
- 0.016 ± 8 × 10 − 4
- numeric value
- 0.016
- uncertainty
- type: standard_deviation; value: 0.0008
- source locator
- Table 3, row(Linear), column(RMSE, mean rank)
- missing metadata
- denominator: unextracted; seeds: unreported
- review
- method: Deterministic parse of the pinned HTML tables, with row and column counts asserted; reviewer: Codex research agent; no human review claimed; date: 2026-09-18; artifact sha256: 5c4804565dd9faa17a11853a79e9847dcb6da73715b4c91f62e5b274cc79f186; retrieval url: https://arxiv.org/html/2408.10609v1; notes: Source checked, not reproduced. Metrics differ by task, so no composite score across tasks is computed or implied.