0.88 AUROC
scRegNet (scBERT backbone) · AUROC · hESC cell-type-specific GRN
- Tested pipeline
- scRegNet (scBERT backbone)
- Task
- Gene-regulatory link prediction
- Dataset
- hESC cell-type-specific GRN
- Procedure
- TFs plus 500 variable genes; mean from 50 independent evaluations.
- Evaluation
- scRegNet (scBERT backbone): Gene-regulatory link prediction
- Coverage
- scored: unreported; eligible: unreported
- Uncertainty
- ± 0.00 as printed
- Evidence
- Author-reported evaluation · source checkedPrediction of Gene Regulatory Connections with Joint Single-Cell Foundation Models and Graph-Based Learning · Table 2, scRegNet (w/ scBERT) row, hESC AUROC entry
A source-checked result verifies the numerical transcription, not every model or protocol detail. Evaluation metadata: needs review. Source checked does not mean independently reproduced.
Reproduction
- Split
- Not reported
- Adaptation
- Not reported
- Scoring implementation
- Not reported
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.
Evidence
Source checking verifies the cited claim or transcription. It does not establish 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 |
|---|---|---|
| attributes.printed_value 0.88 Individual claims | Prediction of Gene Regulatory Connections with Joint Single-Cell Foundation Models and Graph-Based Learning Table 2, scRegNet (w/ scBERT) row, hESC AUROC entry Version: PMC11838224.2 | source checked independent ai table review · 2026-09-16T10:41:16.542807+00:00 author reported Audit detailsRead break elements: cells contain AUROC on first line then AUPRC. Selected hESC (first cell type), first line. Caption specifies 500 most-variable genes and 50 independent evaluations. This verifies the central score at its source location, not every metadata field or an experimental reproduction. Field: Claim: claim-lit-032 Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record Extraction artifact SHA-256: |
Sources and history
View linked audit checks and correction history
Release 2026-09-29-06401fd5b220 · Record review: source checked
1 source records and release history
- Prediction of Gene Regulatory Connections with Joint Single-Cell Foundation Models and Graph-Based Learning · Original source · PMC11838224.2
Technical metadata and extraction receipts
Stable ID: lit-032
- areas
- cells-tissues
- tasks
- Gene-regulatory link prediction
- printed value
- 0.88
- numeric value
- 0.88
- metric
- AUROC
- metric direction
- unknown
- unit
- unitless
- uncertainty
- ± 0.00 as printed
- source locator
- Table 2, scRegNet (w/ scBERT) row, hESC AUROC entry
- review
- method: independent_ai_table_review; reviewer: Codex omics research agent; independent source-table review, not human review; reviewed at: 2026-09-16T10:41:16.542807+00:00; notes: Read break elements: cells contain AUROC on first line then AUPRC. Selected hESC (first cell type), first line. Caption specifies 500 most-variable genes and 50 independent evaluations. This verifies the central score at its source location, not every metadata field or an experimental reproduction.; evidence: {"table_xml_id": "T2", "row_cells": ["scRegNet (w/ scBERT)", "AUROCAUPRC", "0.88±0.000.61±0.00", "0.90±0.000.83±0.00", "0.75±0.010.12±0.01", "0.92±0.000.84±0.00", "0.92±0.000.94±0.00", "0.92±0.000.93±0.00", "0.85±0.010.85±0.01"], "selected_cell_zero_based": 2, "selected_cell_xml": "<td align=\"center\" valign=\"top\" rowspan=\"1\" colspan=\"1\">0.88±0.00<break />0.61±0.00</td>", "caption": "Link prediction performance on seven scRNA-seq datasets with 500 most-variable genes. Each dataset includes a cell-type-specific ground-truth network. The values reported are averages from 50 independent evaluations per cell type. scRegNet utilizing the three backbone models—scBERT, Geneformer, and scFoundation—consistently outperforms the baselines."}; artifact sha256: 65b3272d47bb9c4ee1e7a965169bef63add9dbeb31508d4076e5145b761af4ec; retrieval url: https://www.ebi.ac.uk/europepmc/webservices/rest/PMC11838224/fullTextXML
- legacy id
- lit-032
- legacy row
- id: lit-032; paper id: scregnet-2025; domain id: cells-tissues; task: Gene-regulatory link prediction; model: scRegNet (scBERT backbone); model version: Not reported; dataset: hESC cell-type-specific GRN; dataset version: Not reported; split: Not reported; metric: AUROC; value: 0.88; unit: unitless; uncertainty: ± 0.00 as printed; protocol: TFs plus 500 variable genes; mean from 50 independent evaluations.; source locator: Table 2, scRegNet (w/ scBERT) row, hESC AUROC entry; source url: https://pmc.ncbi.nlm.nih.gov/articles/PMC11838224/; evaluation origin: author_reported; reviewed utc: 2026-09-15T23:25:00Z
- missing metadata
- model version: not_reported_in_legacy_extract; dataset version: not_reported_in_legacy_extract; split: not_reported_in_legacy_extract