Evaluation

LinearFold: PDB

Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics.

Evaluation results

1 evaluation · 4 results. Different protocols are not a single leaderboard.

Protocol: PDB (RNA secondary structure) · Dataset: PDB RNA set

Sorted by F1 (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	F1	Interaction network fidelity	Precision	Recall
LinearFoldEvaluation	0.718	0.726	0.813	0.672

All 4 result rows with coverage, uncertainty and sources

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Exact evaluated configurations and original reported results
Tested configuration	Protocol and dataset	Finding	Evidence and details
Configuration: LinearFold	Protocol: PDB (RNA secondary structure) Dataset: PDB RNA set	0.726 Interaction network fidelity unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LinearFold: PDB Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics. Aggregation: Not reported Deep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF
Configuration: LinearFold	Protocol: PDB (RNA secondary structure) Dataset: PDB RNA set	0.672 Recall unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LinearFold: PDB Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics. Aggregation: Not reported Deep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2 (Tab2), row 9 LinearFold, column 9: PDB Recall
Configuration: LinearFold	Protocol: PDB (RNA secondary structure) Dataset: PDB RNA set	0.718 F1 unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LinearFold: PDB Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics. Aggregation: Not reported Deep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2 (Tab2), row 9 LinearFold, column 7: PDB F1
Configuration: LinearFold	Protocol: PDB (RNA secondary structure) Dataset: PDB RNA set	0.813 Precision unitless · higher Uncertainty: Not reported by the source Coverage: Not reported scored / Not reported eligible	Independent external evaluation · Source checked Methods, coverage and source LinearFold: PDB Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics. Aggregation: Not reported Deep generalizable prediction of RNA secondary structure via base pair motif energy · Table 2 (Tab2), row 9 LinearFold, column 8: PDB Precision

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Release 2026-11-02-a7f03c9e55a5 · Evidence verified: Not verified

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Evaluation procedure

Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics.

Configuration: LinearFold
Protocol: PDB (RNA secondary structure)
Dataset: PDB RNA set

origin: Independent external evaluation
configuration: commit dated August 29, 2022; default parameters
protocol id: paper-protocol-b8acf180ccd3e67923
dataset version: Not reported
split: Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics.
subset: Not reported
population: count: 116; unit: RNA sequences
aggregation: Not reported
inputs: Not reported
adaptation: commit dated August 29, 2022; default parameters
budget: Not reported
metric implementation: Not reported

Metadata review: needs review. Unreported conditions prevent automatic comparisons.

Reproduction

Split: Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics.
Adaptation: commit dated August 29, 2022; default parameters
Scoring implementation: Not reported

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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.

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One row per statement and cited source. Multiple citations are not independent evaluations. Shared locators are labelled explicitly.

20 evidence rows matching the loaded filters

Claims, original sources and review scope · Release 2026-11-02-a7f03c9e55a5
Property and statement	Original source and location	Review and provenance
Comparison: adaptation commit dated August 29, 2022; default parameters Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	not individually reviewed No individual claim review recorded independent paper Audit details Field: `attributes.comparison.adaptation` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: aggregation Not reported Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	missing or unspecified No individual claim review recorded independent paper Audit details Field: `attributes.comparison.aggregation` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: budget Not reported Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	missing or unspecified No individual claim review recorded independent paper Audit details Field: `attributes.comparison.budget` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: dataset version Not reported Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	missing or unspecified No individual claim review recorded independent paper Audit details Field: `attributes.comparison.dataset_version` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: inputs Not reported Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	missing or unspecified No individual claim review recorded independent paper Audit details Field: `attributes.comparison.inputs` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: metric implementation Not reported Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	missing or unspecified No individual claim review recorded independent paper Audit details Field: `attributes.comparison.metric_implementation` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: population: count 116 Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	not individually reviewed No individual claim review recorded independent paper Audit details Field: `attributes.comparison.population.count` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: population: unit RNA sequences Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	not individually reviewed No individual claim review recorded independent paper Audit details Field: `attributes.comparison.population.unit` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: protocol id paper-protocol-b8acf180ccd3e67923 Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	not individually reviewed No individual claim review recorded independent paper Audit details Field: `attributes.comparison.protocol_id` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact
Comparison: split Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics. Context-only references	Deep generalizable prediction of RNA secondary structure via base pair motif energy Original source ↗ Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF Version: version of record Retrieved: 2026-09-16T10:41:16.502000+00:00	not individually reviewed No individual claim review recorded independent paper Audit details Field: `attributes.comparison.split` Source artifact SHA-256: `976218bd172998a1a6e7ed1609ecb8cb2ee380fb48a8dc7b25bc05ea8b0a49af` Hash scope: Hash scope not separately documented; inspect source record Inspected artifact

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Release 2026-11-02-a7f03c9e55a5 · Record review: needs review

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Deep generalizable prediction of RNA secondary structure via base pair motif energy · Original source · version of record

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Technical metadata and extraction receipts

Stable ID: paper-evaluation-290a2c9298ab8eec28

areas: rna-transcriptomes
tasks: RNA secondary structure
origin: independent_paper
protocol: Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics.
version: commit dated August 29, 2022; default parameters
comparison: protocol id: paper-protocol-b8acf180ccd3e67923; dataset version: Not reported; split: Family-wise RNA secondary-structure evaluation; macro-average canonical base-pair metrics.; subset: Not reported; population: count: 116; unit: RNA sequences; aggregation: Not reported; inputs: Not reported; adaptation: commit dated August 29, 2022; default parameters; budget: Not reported; metric implementation: Not reported
source locator: Family-wise evaluation of three DL methods (BPfold, SPOT-RNA, and MXfold2), three shallow learning methods (ContextFold, CONTRAfold, and EternaFold) and non-learning methods (LinearFold, RNAfold, SimFold, and RNAstructure) on Rfam12.3–14.10 ( n = 10,791 RNAs) and PDB ( n = 116 RNAs) datasets; Table 2 (Tab2), row 3 BPfold, column 6: PDB INF; Table 2 (Tab2), row 4 SPOT-RNA, column 6: PDB INF; Table 2 (Tab2), row 5 MXfold2, column 6: PDB INF; Table 2 (Tab2), row 6 ContextFold, column 6: PDB INF; Table 2 (Tab2), row 7 CONTRAfold, column 6: PDB INF; Table 2 (Tab2), row 8 EternaFold, column 6: PDB INF; Table 2 (Tab2), row 9 LinearFold, column 6: PDB INF; Table 2 (Tab2), row 10 RNAfold, column 6: PDB INF; Table 2 (Tab2), row 11 SimFold, column 6: PDB INF; Table 2 (Tab2), row 12 RNAstructure, column 6: PDB INF
missing metadata: budget: reason: unreported; checkpoint revision: reason: unextracted; split manifest: reason: unextracted

Related records

system: LinearFold
assessment: PDB (RNA secondary structure)
data: PDB RNA set
evaluation: LinearFold: INF on PDB
evaluation: LinearFold: Recall on PDB
evaluation: LinearFold: F1 on PDB
evaluation: LinearFold: Precision on PDB

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