Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays)

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22 recorded evaluations, 22 metric rows. A comparison chart has not yet been validated for these results. The table retains the individual findings and their sources.

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All evaluations

22 evaluations · 22 results. Different protocols are not a single leaderboard.

Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) · Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)

Sorted by MCC (WT-LLR; median over assays) (higher is better). The best value in each column is highlighted. Decimals are rounded for display; each value links to the printed value and its source.

Tested configuration	MCC (WT-LLR; median over assays)
SpliceBERT (zero-shot, Wang et al. 2026)Evaluation	0.176 (best in column)
RNA-FM (zero-shot, Wang et al. 2026)Evaluation	0.172
DGRNA (zero-shot, Wang et al. 2026)Evaluation	0.163
AIDO.RNA (1.6B) (zero-shot, Wang et al. 2026)Evaluation	0.155
MP-RNA (zero-shot, Wang et al. 2026)Evaluation	0.143
AIDO.RNA (650M) (zero-shot, Wang et al. 2026)Evaluation	0.122
Uni-RNA (L8) (zero-shot, Wang et al. 2026)Evaluation	0.115
PlantRNA-FM (zero-shot, Wang et al. 2026)Evaluation	0.112
Uni-RNA (L12) (zero-shot, Wang et al. 2026)Evaluation	0.108
RiNALMo (mega) (zero-shot, Wang et al. 2026)Evaluation	0.104
Uni-RNA (L16) (zero-shot, Wang et al. 2026)Evaluation	0.1
RNAErnie (zero-shot, Wang et al. 2026)Evaluation	0.099
RiNALMo (giga) (zero-shot, Wang et al. 2026)Evaluation	0.095
RiNALMo (micro) (zero-shot, Wang et al. 2026)Evaluation	0.092
LucaOne (D17.6M) (zero-shot, Wang et al. 2026)Evaluation	0.076
LucaOne (D36.0M) (zero-shot, Wang et al. 2026)Evaluation	0.074
LAMAR (4k) (zero-shot, Wang et al. 2026)Evaluation	0.07
ProtRNA (zero-shot, Wang et al. 2026)Evaluation	0.067
UTR_LM (zero-shot, Wang et al. 2026)Evaluation	0.063
LAMAR (2k) (zero-shot, Wang et al. 2026)Evaluation	0.062
LucaOne (G36.8M) (zero-shot, Wang et al. 2026)Evaluation	0.059
RNABERT (zero-shot, Wang et al. 2026)Evaluation	0.044

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Tested model or methodProtocolDatasetEvaluation setupMetricEvidence origin

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: AIDO.RNA (1.6B) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.155 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source AIDO.RNA (1.6B) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'AIDO.RNA (1.6B)', column 'MCC' (Median)
Configuration: AIDO.RNA (650M) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.122 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source AIDO.RNA (650M) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'AIDO.RNA (650M)', column 'MCC' (Median)
Configuration: DGRNA (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.163 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source DGRNA zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'DGRNA', column 'MCC' (Median)
Configuration: LAMAR (2k) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.062 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LAMAR (2k) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'LAMAR (2k)', column 'MCC' (Median)
Configuration: LAMAR (4k) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.07 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LAMAR (4k) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'LAMAR (4k)', column 'MCC' (Median)
Configuration: LucaOne (D17.6M) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.076 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LucaOne (D17.6M) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'LucaOne (D17.6M)', column 'MCC' (Median)
Configuration: LucaOne (D36.0M) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.074 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LucaOne (D36.0M) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'LucaOne (D36.0M)', column 'MCC' (Median)
Configuration: LucaOne (G36.8M) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.059 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LucaOne (G36.8M) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'LucaOne (G36.8M)', column 'MCC' (Median)
Configuration: MP-RNA (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.143 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source MP-RNA zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'MP-RNA', column 'MCC' (Median)
Configuration: PlantRNA-FM (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.112 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source PlantRNA-FM zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'PlantRNA-FM', column 'MCC' (Median)
Configuration: ProtRNA (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.067 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source ProtRNA zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'ProtRNA', column 'MCC' (Median)
Configuration: RiNALMo (giga) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.095 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source RiNALMo (giga) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'RiNALMo (giga)', column 'MCC' (Median)
Configuration: RiNALMo (mega) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.104 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source RiNALMo (mega) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'RiNALMo (mega)', column 'MCC' (Median)
Configuration: RiNALMo (micro) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.092 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source RiNALMo (micro) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'RiNALMo (micro)', column 'MCC' (Median)
Configuration: RNA-FM (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.172 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source RNA-FM zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'RNA-FM', column 'MCC' (Median)
Configuration: RNABERT (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.044 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source RNABERT zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'RNABERT', column 'MCC' (Median)
Configuration: RNAErnie (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.099 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source RNAErnie zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'RNAErnie', column 'MCC' (Median)
Configuration: SpliceBERT (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.176 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source SpliceBERT zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'SpliceBERT', column 'MCC' (Median)
Configuration: Uni-RNA (L12) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.108 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source Uni-RNA (L12) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'Uni-RNA (L12)', column 'MCC' (Median)
Configuration: Uni-RNA (L16) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.1 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source Uni-RNA (L16) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'Uni-RNA (L16)', column 'MCC' (Median)
Configuration: Uni-RNA (L8) (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.115 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source Uni-RNA (L8) zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'Uni-RNA (L8)', column 'MCC' (Median)
Configuration: UTR_LM (zero-shot, Wang et al. 2026)	Protocol: Wang et al. 2026 zero-shot fitness, RNAGym ncRNA DMS assays (31 assays), WT-LLR, MCC (median over assays) Dataset: RNAGym ncRNA DMS assays (31 assays) (Wang et al. 2026)	0.063 MCC (WT-LLR; median over assays) unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source UTR_LM zero-shot fitness on RNAGym ncRNA DMS assays (31 assays) (WT-LLR, MCC, median) lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median Aggregation: Not reported Zero-shot benchmarking of RNA language models: Supplementary Information; Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Supplementary Table 10, row 'UTR_LM', column 'MCC' (Median)

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Zero-shot benchmarking of RNA language models: Supplementary Information · Original source · bbag098_supplymentary_information_20260209.docx from the Europe PMC supplementary files archive for PMC12963973
Zero-shot benchmarking of RNA language models in structural, functional, and evolutionary learning · Original source · Briefings in Bioinformatics 2026, bbag098 (issue date 2026-03-01); PMC12963973 full-text XML

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Technical metadata and extraction receipts

Stable ID: lit-rna-20261011-rnalm-zeroshot-protocol-t10-mcc-median

areas: rna-transcriptomes
contexts: research
protocol: Zero-shot: wild-type conditioned log-likelihood ratio from token logits. Metric MCC, median over assays.
version: Wang et al. 2026
metric: matthews-correlation-coefficient
metric direction: higher
unit: unitless
metric qualifier: WT-LLR; median over assays
source locator: Supplementary Table 10 caption and column 'MCC'; main text Methods
limitations: Zero-shot only; no fine-tuning or task head.; Binarisation for MCC, F1 and AUC in the fitness task is not described in the main text or supplement.

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