Strengths and considerations
No source-reviewed explanatory claims are recorded here yet.
model · method
scVI
scVI is the method recorded for Cross-dataset single-cell drug response transfer. This page preserves the configuration reported by scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning.
At a glance
Explanatory profile: limited source coverage · Automated source review, 2026-09-16. This does not change the review status of its results.
| Property | Description and evidence |
|---|---|
| Recorded dataset | scXDR transfer scenario 2scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning · Table 2, scVI row, Scenario 2 column |
| Model type | Not extracted or verified for this record. |
| Known versions | Not extracted or verified for this record. |
| Training data | Not extracted or verified for this record. |
| Context limits | Not extracted or verified for this record. |
| Access | Not extracted or verified for this record. |
| Code licence | Not extracted or verified for this record. |
| Weights licence | Not extracted or verified for this record. |
How it works
Recorded evaluation
The imported evaluation describes this procedure: Single-cell-to-single-cell transfer; source scenario 2.
scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning · Table 2, scVI row, Scenario 2 columnBenchmarks and results
Release 2026-09-16-d74d282221a9 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| scVI: Cross-dataset single-cell drug response transfer Model: scVI · Benchmark: Cross-dataset single-cell drug response transfer · Dataset: scXDR transfer scenario 2 Single-cell-to-single-cell transfer; source scenario 2. Independent external evaluation · Evaluation metadata: needs review | ||
| 0.6970 AUC Unit: unitless · Direction: unknown | Uncertainty: ± 0.2463 standard deviation Scored: Not reported · Eligible: Not reported | source checkedscXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning · Table 2, scVI row, Scenario 2 column Source checking is not independent reproduction. |
Strengths and limitations
Limitations and conditions
- This is an evidence-limited profile. The recorded evaluation context does not establish performance on other datasets or configurations.scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning · Table 2, scVI row, Scenario 2 column
Profile review details
Reviewed the existing release record, its source pointer and linked evaluation context. This is not a fresh full-text architecture review or independent reproduction; numerical review status is unchanged.
Stable record: reported-model-f23306b94dc7b6Sources and history
Release 2026-09-16-d74d282221a9 · Record review: needs review
- scXDR: drug response prediction across single-cell datasets via heterogeneous network transfer learning · Original source · PMC archival version PMC12859067.1
Technical metadata and extraction receipts
Stable ID: reported-model-f23306b94dc7b6
- areas
- cells-tissues
- entity level
- method
- version
- Not reported
- reported name
- scVI
- missing metadata
- version: not_reported_in_legacy_extract; checkpoint revision: not_reported_in_legacy_extract; training data: not_reported_in_legacy_extract; licence: not_reported_in_legacy_extract