{"id":"W4248810377","doi":"10.12688/f1000research.13535.2","title":"StateHub-StatePaintR: rapid and reproducible chromatin state evaluation for custom genome annotation","year":2020,"lang":"en","type":"preprint","venue":"F1000Research","topic":"Genomics and Chromatin Dynamics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"National Institutes of Health","keywords":"Annotation; Epigenomics; Genome; Chromatin; Computational biology; Biology; Genomics; Epigenome; Computer science; Genetics; DNA methylation; Gene","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004711743,0.00244039,0.002013856,0.002465192,0.001542436,0.003470549,0.003616151,0.001902052,0.05444474],"category_scores_gemma":[0.011924,0.002760028,0.002293743,0.002795536,0.0007309059,0.00300471,0.003893224,0.003668023,0.02706527],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001861046,"about_ca_system_score_gemma":0.002463282,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005534543,"about_ca_topic_score_gemma":0.01327038,"domain_scores_codex":[0.9976031,0.0003266008,0.0002238027,0.0007830252,0.000885469,0.0001780045],"domain_scores_gemma":[0.9961221,0.001665482,0.0003221838,0.001116144,0.0005620872,0.0002120988],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.001931323,0.0001364936,0.006661163,0.002330967,0.0004753518,0.0006268618,0.0009021608,0.008550648,0.09310753,0.01300407,0.7172269,0.1550464],"study_design_scores_gemma":[0.0008004816,0.0002331531,0.0123905,0.0005574623,0.0002309149,0.0007889361,0.0003308744,0.1254313,0.2207562,0.03404955,0.6038189,0.00061168],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01160347,0.0006385316,0.4229444,0.0007974721,0.0007295748,0.0005120487,0.1567366,0.3958832,0.01015478],"genre_scores_gemma":[0.05666944,0.0006647361,0.5406466,0.0008799598,0.000135251,0.002426208,0.2483747,0.1390461,0.01115706],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.05444474,"threshold_uncertainty_score":0.1821358,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04904147326376352,"score_gpt":0.3399677459246874,"score_spread":0.2909262726609239,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}