Noncoding RNA-pair classification evaluates a strongly imbalanced interaction dataset with validation-tuned decision thresholds.
Explanatory profile: limited source coverage · Automated source review, 2026-09-16. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Datasets | RNA-KG-derived multispecies interaction pairs; sampled negatives preserve pair-type frequencies with a 20:1 negative-to-positive ratio.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Splits | Stratified 90:10 train/test partition; a further validation subset is drawn from training data.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Metrics | Accuracy, balanced accuracy, precision, recall, F1, AUROC and AUPRC, both overall and by interacting pair type.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Baselines | Random classifier, IntaRNA and CUPID pooling/data-augmentation ablations.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Leakage controls | The threshold is selected by validation MCC; sequence-disjoint separation of interacting entities remains unextracted.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Uncertainty | The cited text-accessible evaluation sections give no confidence-interval, resampling or repeat-run error-bar specification. Image-only tables and uninspected supplements are outside this absence claim. · Not reported in inspected sourcesSourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Entity type | Paper-specific computational evaluation protocol.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Organisms | Multiple species represented in RNA-KG.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Assays | RNA–RNA interaction annotations with sampled negative pairs.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Allowed inputs | Pairs of noncoding RNA sequences.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
| Adaptation | Supervised pair classification using a stratified train/test partition and training-derived validation subset.SourcesComputational understanding of non-coding RNA pairwise interactions · Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages |
Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol.
RNA-KG-derived multispecies interaction pairs; sampled negatives preserve pair-type frequencies with a 20:1 negative-to-positive ratio. Stratified 90:10 train/test partition; a further validation subset is drawn from training data. Accuracy, balanced accuracy, precision, recall, F1, AUROC and AUPRC, both overall and by interacting pair type. Random classifier, IntaRNA and CUPID pooling/data-augmentation ablations. The threshold is selected by validation MCC; sequence-disjoint separation of interacting entities remains unextracted. The cited text-accessible evaluation sections give no confidence-interval, resampling or repeat-run error-bar specification. Image-only tables and uninspected supplements are outside this absence claim.
Each evaluation records what was tested and under which conditions.
Release 2026-09-17-d277315f7d76 · 1 evaluation · 1 metric row. Different protocols are not a single leaderboard.
| Metric and finding | Coverage and uncertainty | Evidence |
|---|---|---|
| CUPID Data-aug-Avg: non-coding RNA pairwise interaction prediction Pipeline: CUPID Data-aug-AvgTask: non-coding RNA pairwise interaction predictionDataset: ncRNA interaction pairs Data augmentation with average pooling for molecule-level ncRNA embeddings Author-reported evaluation · Evaluation metadata: needs review | ||
| 0.919 AUROC Unit: fraction · Direction: unknown | Uncertainty: not reported in legacy extract Scored: Not reported · Eligible: Not reported | source checkedComputational understanding of non-coding RNA pairwise interactions · Table 1, CUPID > Data-aug-Avg row, AUROC column Source checking is not independent reproduction. |
Last literature check: 2026-09-17. Primary-paper discovery and source inspection. Source-checked results are not independently reproduced experiments.
| Paper or primary resource | Version | Reference |
|---|---|---|
| Computational understanding of non-coding RNA pairwise interactions | PMC archival version PMC12957212.1 | Read source DOI: 10.3389/frai.2026.1749205 |
primary comparison table screened
Task-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced.
Stable record: reported-task-c7ce06b753b8b6Trace 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.
18 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Diagram caption Conceptual summary of the cited evaluation; exact task configuration and source version remain part of the protocol. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram steps ["Input: Pairs of noncoding RNA sequences.","Evaluation: Supervised pair classification using a stratified train/test partition and training-derived validation subset.","Readout: Accuracy, balanced accuracy, precision, recall, F1, AUROC and AUPRC, both overall and by interacting pair type."] Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Diagram title Computational evaluation flow Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Datasets RNA-KG-derived multispecies interaction pairs; sampled negatives preserve pair-type frequencies with a 20:1 negative-to-positive ratio. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Splits Stratified 90:10 train/test partition; a further validation subset is drawn from training data. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Adaptation Supervised pair classification using a stratified train/test partition and training-derived validation subset. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Metrics Accuracy, balanced accuracy, precision, recall, F1, AUROC and AUPRC, both overall and by interacting pair type. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Baselines Random classifier, IntaRNA and CUPID pooling/data-augmentation ablations. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Leakage controls The threshold is selected by validation MCC; sequence-disjoint separation of interacting entities remains unextracted. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | source checked automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Uncertainty The cited text-accessible evaluation sections give no confidence-interval, resampling or repeat-run error-bar specification. Image-only tables and uninspected supplements are outside this absence claim. Individual claims | Computational understanding of non-coding RNA pairwise interactions Methods: Dataset; Experimental evaluation: Data preparation and splitting; Evaluation metrics; cached text lines 15–17, 66–75; comparative evaluation and ablation passages Version: PMC archival version PMC12957212.1 | unreported automated source review · 2026-09-16 Audit detailsTask-specific computational methodology and field context checked in the cited primary-source artifact. Source-backed fields, inapplicable evaluator dimensions and unresolved details are distinguished. Numerical results were not reproduced. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Release 2026-09-17-d277315f7d76 · Record review: needs review
Stable ID: reported-task-c7ce06b753b8b6