Strengths and considerations
No source-reviewed explanatory claims are recorded here yet.
Protocol
Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction)
Human RNA 2OMe sites, five-fold cross-validation · ACC. 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.
Sources
2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACCOverview
Key specifications have not been extracted for this record. See the linked evaluation and sources for the reported setup.
limited source coverage · Automated source review, 2026-09-17. All specifications and missing details
Results
Each comparison retains its reviewed evaluation scope, dataset and metric. Results are shown without a pooled ranking.
Human RNA 2OMe sites, five-fold cross-validation · ACC
ACC (fraction) · Higher values are better.
Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) · human RNA 2OMe sites
Evidence origin: Author-reported evaluation.
2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC- Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.
Comparison details and limitations
41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.
Automated source review: 2026-09-17. 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 7 of 7 matching rows.
Tested configuration
00.250.50.751
Reported scoreMethods and evaluation design
Procedure, tasks and evaluated configurations
How it works
Evaluation in this paper
41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.
Sources
2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACCEvaluation design
Benchmarks bring together tasks and protocols. A task describes the biological question; a protocol defines a particular test.
These source-backed links do not make different protocols or scores interchangeable.
Recorded evaluations
Each evaluation records what was tested and under which conditions.
- 2OMe-LM: human RNA 2-prime-O-methylation site prediction
- Word2vec + MLP: Human RNA 2OMe sites, five-fold cross-validation
- GloVe + TextCNN + MLP: Human RNA 2OMe sites, five-fold cross-validation
- GloVe + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation
- GloVe + MLP: Human RNA 2OMe sites, five-fold cross-validation
- Word2vec + TextCNN + MLP: Human RNA 2OMe sites, five-fold cross-validation
- Word2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation
Baseline coverage
Reference methods help show what a model adds beyond simple controls. We track a null control and a conventional method for each protocol.
0 of 2 active baseline roles have published Rewire measurements in this release. Measurements on a selected protocol do not establish coverage of an entire suite.
No execution recipe linked to this protocol. Recipe availability does not establish a completed evaluation.
No reviewed evaluations with results linked in this release.
Literature evidence is not a Rewire measurement. Executed but unpublished runs and private review status are not included.
Null control
Proposed control: requires review
Protocol-valid structural control
Protocol-specific applicability, permitted inputs, access, split, evaluator and execution requirements need review before implementation or execution.
This is a suggested selection rule, not a validated method or a measured score.
Conventional reference
Proposed control: requires review
Thermodynamic folding with protocol-compatible input constraints
Protocol-specific applicability, permitted inputs, access, split, evaluator and execution requirements need review before implementation or execution.
This is a suggested selection rule, not a validated method or a measured score.
Protocol coverage CSV · Model evaluation matrix · Source table · Release and checksums
Coverage is derived from release 2026-09-29-06401fd5b220. Source citations describe the original records; they do not validate an unreviewed baseline proposal. No results have been generated by this audit.
Run instructions
No runnable recipe has been reviewed for this protocol. Dataset access, model requirements, licences and compute requirements must be checked against its sources before execution.
Strengths, limitations and unresolved questions
Strengths and limitations
Limitations and conditions
No source-reviewed explanatory claims are recorded here yet.
Profile review details
Primary-source transcription and separate automated review. No human sign-off or experimental reproduction.
Stable record: paper-protocol-1e891689a18fea3b65Specifications
Inputs, training, access and other details
Explanatory profile: limited source coverage · Automated source review, 2026-09-17. Review applies to the cited claims; unresolved fields are listed below. Numerical results retain their own review status.
| Property | Description and evidence |
|---|---|
| Datasets | Not extracted or verified for this record. |
| Organisms | Not extracted or verified for this record. |
| Assays | Not extracted or verified for this record. |
| Splits | Not extracted or verified for this record. |
| Allowed inputs | Not extracted or verified for this record. |
| Adaptation | Not extracted or verified for this record. |
| Metrics | Not extracted or verified for this record. |
| Baselines | Not extracted or verified for this record. |
Evidence
Source checking verifies the cited claim or transcription. It does not establish independent reproduction.
Papers and result coverage
Last literature check: 2026-09-17. Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.
| Paper or primary resource | Version | Reference |
|---|---|---|
| 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model | journal full text in PMC | Read source DOI: 10.1093/bioinformatics/btaf417 |
Historical gaps recorded on 2026-09-17
The catalogue now holds 49 result rows for this benchmark. A note below about pending extraction describes the state on 2026-09-17 and may since have been answered by a later batch. The result rows and their sources are the current record.
- exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.
Search and extraction details
complete tables extracted
Searches
- 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model 10.1093/bioinformatics/btaf417
Evidence locations
- Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC
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.
3 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Evaluation in this paper 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set. Individual claims | 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC Version: journal full text in PMC | source checked automated source review · 2026-09-17 Audit detailsPrimary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Introduction Human RNA 2OMe sites, five-fold cross-validation · ACC. 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set. Individual claims | 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC Version: journal full text in PMC | source checked automated source review · 2026-09-17 Audit detailsPrimary-source transcription and separate automated review. No human sign-off or experimental reproduction. Field: Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
| Relationship: evaluates task reported-task-82fc7843f07324 Individual claims | 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC Version: journal full text in PMC | source checked automated source review · 2026-09-17 Audit detailsField: Claim: paper-claim-57f32b2ec51b3e840d Source artifact SHA-256: Hash scope: Hash scope not separately documented; inspect source record |
Sources and history
View linked audit checks and correction history
Release 2026-09-29-06401fd5b220 · Record review: needs review
1 source records and release history
- 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Original source · journal full text in PMC
Technical metadata and extraction receipts
Stable ID: paper-protocol-1e891689a18fea3b65
- areas
- rna-transcriptomes
- tasks
- human RNA 2-prime-O-methylation site prediction
- entity level
- protocol
- protocol
- 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.
- comparison panels
- id: 2ome-lm-2025-btaf417-t1-accuracy; title: Human RNA 2OMe sites, five-fold cross-validation · ACC; protocol id: paper-protocol-1e891689a18fea3b65; dataset id: reported-dataset-bd3d8e7d6cd196; metric: ACC; unit: fraction; direction: higher; result ids: paper-result-d7aa3ed3ecdcfb7659; paper-result-7eeb7cd00870d4b822; paper-result-975e1e3b3cef0095d6; paper-result-bd40af36b346c6babe; paper-result-212ef20ae0523df179; paper-result-40dcbc4ba963adc002; paper-result-4bf3c3f0eec618c5cf; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; context: 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.; caveats: Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: 2ome-lm-2025-btaf417-t1-F1; title: Human RNA 2OMe sites, five-fold cross-validation · F1-score; protocol id: paper-protocol-1e891689a18fea3b65; dataset id: reported-dataset-bd3d8e7d6cd196; metric: F1-score; unit: fraction; direction: higher; result ids: paper-result-7fa777341a7b054db1; paper-result-db5c42675cc3446cac; paper-result-3b51683bec36f2abaa; paper-result-5a1e3c197818f5eef1; paper-result-3b60f80651245fd9b6; paper-result-5a0302f7287f4744fe; paper-result-98d984a2c66d9da9cc; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score; Table 1. (btaf417-T1), row 8 2OMe-LM, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score; context: 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.; caveats: Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: 2ome-lm-2025-btaf417-t1-precision; title: Human RNA 2OMe sites, five-fold cross-validation · Precision; protocol id: paper-protocol-1e891689a18fea3b65; dataset id: reported-dataset-bd3d8e7d6cd196; metric: Precision; unit: fraction; direction: higher; result ids: paper-result-3eeedfbb867730e5ae; paper-result-1acfee83326c80f579; paper-result-edd616527eedbbdd6e; paper-result-5b8226a4362a18dc2f; paper-result-3265bdf784a6414dad; paper-result-e4f14db506e688bbf3; paper-result-2fdf47de24865482a1; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision; Table 1. (btaf417-T1), row 8 2OMe-LM, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision; context: 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.; caveats: Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: 2ome-lm-2025-btaf417-t1-recall; title: Human RNA 2OMe sites, five-fold cross-validation · Recall; protocol id: paper-protocol-1e891689a18fea3b65; dataset id: reported-dataset-bd3d8e7d6cd196; metric: Recall; unit: fraction; direction: higher; result ids: paper-result-a63abaf273d6997c8f; paper-result-c3fa62647b4acefdab; paper-result-ff7373a626f7495c54; paper-result-dbd9c2c21ebea1c98f; paper-result-e56df473e582088515; paper-result-dca07f72da08e9b1aa; paper-result-671f931ffacbf39ee5; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall; Table 1. (btaf417-T1), row 8 2OMe-LM, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall; context: 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.; caveats: Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: 2ome-lm-2025-btaf417-t1-AUROC; title: Human RNA 2OMe sites, five-fold cross-validation · AUC; protocol id: paper-protocol-1e891689a18fea3b65; dataset id: reported-dataset-bd3d8e7d6cd196; metric: AUC; unit: fraction; direction: higher; result ids: paper-result-d2c72c9538f864b13d; paper-result-5046ce3e5b1283c839; paper-result-138834d6ec841f6c4d; paper-result-928adade90586a2477; paper-result-b3a1db1d2e30c1ab66; paper-result-9ce02fe7f446cb3868; b2-2ome-lm-2025; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC; context: 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.; caveats: Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: 2ome-lm-2025-btaf417-t1-AUPRC; title: Human RNA 2OMe sites, five-fold cross-validation · AUPR; protocol id: paper-protocol-1e891689a18fea3b65; dataset id: reported-dataset-bd3d8e7d6cd196; metric: AUPR; unit: fraction; direction: higher; result ids: paper-result-256879a6ad6287f562; paper-result-cca7eb69b40055db2f; paper-result-a14ee136864e50bd74; paper-result-da3bae3411f4589cf5; paper-result-17e76530dee5b1fe4f; paper-result-84c2a332b94869bbbe; paper-result-18ce292cd466151112; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR; Table 1. (btaf417-T1), row 8 2OMe-LM, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR; context: 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.; caveats: Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17; id: 2ome-lm-2025-btaf417-t1-MCC; title: Human RNA 2OMe sites, five-fold cross-validation · MCC; protocol id: paper-protocol-1e891689a18fea3b65; dataset id: reported-dataset-bd3d8e7d6cd196; metric: MCC; unit: unitless; direction: higher; result ids: paper-result-9f3d430c64f27de03d; paper-result-038d30f130b6a4c64b; paper-result-2ca6b64f9aa1a9748e; paper-result-e408a58902cb9dc5bf; paper-result-93ccc046cae95aea0c; paper-result-fe6771186123a657fd; paper-result-71c551bcf9091644da; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC; context: 41-nt centred RNA windows; balanced 8,037 positive and 8,037 negative samples after 80% identity filtering, then 8:2 train/test division. Average of five validation folds of the training set.; caveats: Do not pool cross-validation and independent-test scores. The 8:2 ratio is not converted into an exact test count. Training-data overlap for pre-existing predictors is not established by this table. Origins are labelled per method; appearance in one table does not constitute independent replication of every model.; review: method: automated_source_review; date: 2026-09-17
- benchmark research
- review date: 2026-09-17; status: complete_tables_extracted; primary sources: 2ome-lm-2025; inspected locators: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; searched queries: 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model 10.1093/bioinformatics/btaf417; gaps: exact checkpoint hashes and per-method scored denominators: Table labels alone do not establish these fields; do not infer checkpoint or scored count from model name or dataset size.; claim scope: Dated primary-source discovery and protocol/table screening. Source checking does not mean experimental reproduction. Only separately extracted and independently reviewed numeric batches are publishable.
- legacy kinds
- benchmark
- entity classification
- review date: 2026-09-17; rationale: The source-backed record identifies a specified evaluated procedure and its dataset/split/scoring context. Classify it as a protocol while preserving version and comparison restrictions.; source ids: 2ome-lm-2025; source locator: Performance comparison of 2OMe-LM and deep learning baseline models using 5-fold CV. a; Table 1. (btaf417-T1), row 2 GloVe + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 3 GloVe + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 4 GloVe + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 5 Word2vec + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 6 Word2vec + TextCNN + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; Table 1. (btaf417-T1), row 8 2OMe-LM, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; ambiguities: None recorded
Related records
- evaluates task: human RNA 2-prime-O-methylation site prediction
- benchmark: 2OMe-LM: human RNA 2-prime-O-methylation site prediction
- subject: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction): links:evaluates_task:reported-task-82fc7843f07324
- benchmark: Word2vec + MLP: Human RNA 2OMe sites, five-fold cross-validation
- benchmark: GloVe + TextCNN + MLP: Human RNA 2OMe sites, five-fold cross-validation
- benchmark: GloVe + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation
- benchmark: GloVe + MLP: Human RNA 2OMe sites, five-fold cross-validation
- benchmark: Word2vec + TextCNN + MLP: Human RNA 2OMe sites, five-fold cross-validation
- benchmark: Word2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation