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PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean

covariate transfer on Srivatsan20, RMSE of the mean. Scored with RMSE of the mean on Srivatsan20. 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.

10 evaluations · 10 results

Overview

covariate transfer on Srivatsan20, RMSE of the mean. Scored with RMSE of the mean on Srivatsan20. 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.

Consult the linked sources for architecture or protocol details. Missing evidence is not evidence of a missing capability.

Results

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PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean

rmse_mean (error) · Lower values are better.

PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean · Srivatsan20 (PerturBench split)

Evidence origin: Author-reported evaluation.

PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis · Table 2, column(RMSE, mean)
  • RMSE and both rank metrics are better when lower. The rank metrics measure how often another perturbation's prediction is closer than the right one's.
  • The two experiments use different datasets and splits, so their figures are not comparable to each other.
Comparison details and limitations

Every method PerturBench reports on covariate transfer on Srivatsan20, RMSE of the mean, scored with RMSE of the mean on Srivatsan20.

  • Author-reported numbers, source checked but not independently reproduced.

Automated source review: 2026-09-18. Numerical source review does not establish independent reproduction.

Dots show point estimates. Whiskers show only explicitly defined uncertainty (standard deviation, standard error or a labelled interval); their definitions remain in Table. Unresolved uncertainty is not plotted. Differences do not establish statistical significance.

Showing 10 of 10 matching rows.

Tested configuration
0.01040.04090.07140.1020.133
Reported score
  1. Biolord*0.086 ± 4 × 10 − 2
  2. SAMS-VAE*0.060 ± 1 × 10 − 3
  3. Linear0.030 ± 5 × 10 − 4
  4. Decoder (Cov)0.023 ± 3 × 10 − 5
  5. CPA*0.021 ± 4 × 10 − 4
  6. CPA* (scGPT)0.021 ± 3 × 10 − 4
  7. CPA* (noAdv)0.020 ± 8 × 10 − 4
  8. LA0.018 ± 6 × 10 − 5
  9. Decoder0.018 ± 1 × 10 − 4
  10. LA (scGPT)0.017 ± 1 × 10 − 4

Methods and evaluation design

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Evidence

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Evidence table

Inspect claims, sources and review details

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1 evidence row matching the loaded filters

Claims, original sources and review scope · Release 2026-09-29-06401fd5b220
Property and statementOriginal source and locationReview and provenance
Relationship: part of
discovery-benchmark-perturbench
Individual claims		PerturBench: Benchmarking Machine Learning Models for Cellular Perturbation Analysis

Original source ↗

Table 2, column(RMSE, mean)

Version: Primary full-text snapshot retrieved 2026-09-17; exact bytes pinned by SHA-256
Retrieved: 2026-09-17T08:06:28.400469+00:00

source checked

automated source review · 2026-09-18

Audit details

Primary-source transcription with no human sign-off and no independent reproduction.

Field: links:part_of:discovery-benchmark-perturbench

Claim: perturbench-association-ct-rmse

Source artifact SHA-256: 5c4804565dd9faa17a11853a79e9847dcb6da73715b4c91f62e5b274cc79f186

Hash scope: Exact retrieved primary paper artifact bytes.

Inspected artifact

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Sources and history

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Release 2026-09-29-06401fd5b220 · Record review: source checked

1 source records and release historyDownload this release
Technical metadata and extraction receipts

Stable ID: perturbench-task-ct-rmse

areas
cells-tissues
tasks
covariate transfer on Srivatsan20, RMSE of the mean
metric
RMSE of the mean
metric direction
lower
dataset
Srivatsan20
protocol
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.
source locator
Table 2, column(RMSE, mean)
comparison panels
id: perturbench-panel-ct-rmse; title: PerturBench CT-RMSE: covariate transfer on Srivatsan20, RMSE of the mean; protocol id: perturbench-task-ct-rmse; dataset id: perturbench-dataset-srivatsan20; metric: rmse_mean; unit: error; direction: lower; result ids: perturbench-result-cpa-ct-rmse-rmse-mean; perturbench-result-cpa-noadv-ct-rmse-rmse-mean; perturbench-result-cpa-scgpt-ct-rmse-rmse-mean; perturbench-result-sams-vae-ct-rmse-rmse-mean; perturbench-result-biolord-ct-rmse-rmse-mean; perturbench-result-la-ct-rmse-rmse-mean; perturbench-result-la-scgpt-ct-rmse-rmse-mean; perturbench-result-decoder-ct-rmse-rmse-mean; perturbench-result-decoder-cov-ct-rmse-rmse-mean; perturbench-result-linear-ct-rmse-rmse-mean; source ids: evidence-expansion-perturbench-5c480456; source locator: Table 2, column(RMSE, mean); context: Every method PerturBench reports on covariate transfer on Srivatsan20, RMSE of the mean, scored with RMSE of the mean on Srivatsan20.; caveats: Author-reported numbers, source checked but not independently reproduced.; RMSE and both rank metrics are better when lower. The rank metrics measure how often another perturbation's prediction is closer than the right one's.; The two experiments use different datasets and splits, so their figures are not comparable to each other.; review: method: automated_source_review; date: 2026-09-18
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