Strengths and considerations
No source-reviewed explanatory claims are recorded here yet.
Configuration
Word2Vec + Transformer + MLP
Word2Vec + Transformer + MLP as evaluated in the cited study. Paper-specific predictor; checkpoint not specified
Sources
2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, 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
Evaluations and results
1 evaluation · 7 results. Different protocols are not a single leaderboard.
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| Tested configuration | Protocol and dataset | Finding | Evidence and details |
|---|---|---|---|
| Configuration: Word2Vec + Transformer + MLP | Protocol: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) Dataset: human RNA 2OMe sites | 0.749 ACC fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWord2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation 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. Aggregation: Not reported 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC |
| Configuration: Word2Vec + Transformer + MLP | Protocol: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) Dataset: human RNA 2OMe sites | 0.741 F1-score fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWord2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation 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. Aggregation: Not reported 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 3: Human RNA 2OMe sites, five-fold cross-validation F1-score |
| Configuration: Word2Vec + Transformer + MLP | Protocol: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) Dataset: human RNA 2OMe sites | 0.833 AUPR fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWord2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation 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. Aggregation: Not reported 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 7: Human RNA 2OMe sites, five-fold cross-validation AUPR |
| Configuration: Word2Vec + Transformer + MLP | Protocol: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) Dataset: human RNA 2OMe sites | 0.828 AUC fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWord2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation 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. Aggregation: Not reported 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 6: Human RNA 2OMe sites, five-fold cross-validation AUC |
| Configuration: Word2Vec + Transformer + MLP | Protocol: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) Dataset: human RNA 2OMe sites | 0.718 Recall fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWord2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation 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. Aggregation: Not reported 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 5: Human RNA 2OMe sites, five-fold cross-validation Recall |
| Configuration: Word2Vec + Transformer + MLP | Protocol: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) Dataset: human RNA 2OMe sites | 0.766 Precision fraction · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWord2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation 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. Aggregation: Not reported 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 4: Human RNA 2OMe sites, five-fold cross-validation Precision |
| Configuration: Word2Vec + Transformer + MLP | Protocol: Human RNA 2OMe sites, five-fold cross-validation (human RNA 2-prime-O-methylation site prediction) Dataset: human RNA 2OMe sites | 0.499 MCC unitless · higher Uncertainty: Not reported Coverage: Not reported scored / Not reported eligible | Author-reported evaluation · Source checkedMethods, coverage and sourceWord2Vec + Transformer + MLP: Human RNA 2OMe sites, five-fold cross-validation 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. Aggregation: Not reported 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 8: Human RNA 2OMe sites, five-fold cross-validation MCC |
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Evaluation in this paper
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Sources
2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model · Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACCStrengths, limitations and unresolved questions
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Stable record: paper-model-8c7e871c2468fd5870Specifications
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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.
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2 evidence rows matching the loaded filters
| Property and statement | Original source and location | Review and provenance |
|---|---|---|
| Evaluation in this paper Paper-specific predictor; checkpoint not specified Individual claims | 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, 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 Word2Vec + Transformer + MLP as evaluated in the cited study. Paper-specific predictor; checkpoint not specified Individual claims | 2OMe-LM: predicting 2′-O-methylation sites in human RNA using a pre-trained RNA language model Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, 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 |
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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-model-8c7e871c2468fd5870
- areas
- rna-transcriptomes
- tasks
- human RNA 2-prime-O-methylation site prediction
- entity level
- method
- configuration type
- reported_configuration
- version
- Paper-specific predictor; checkpoint not specified
- legacy kinds
- model
- entity classification
- review date: 2026-09-17; rationale: This source-scoped entry preserves the method/configuration actually named in an evaluation. It is neither a global family identity nor proof of an immutable checkpoint; the linked evaluation retains adaptation, fitting and scoring details.; source ids: 2ome-lm-2025; source locator: Table 1. (btaf417-T1), row 7 Word2Vec + Transformer + MLP, column 2: Human RNA 2OMe sites, five-fold cross-validation ACC; ambiguities: Configuration means the source-labelled evaluated identity. It does not establish missing checkpoint hashes, default settings or equivalence to same-named records in other papers.