{"id":"W1985738984","doi":"10.1093/nar/gkm987","title":"The vertebrate genome annotation (Vega) database","year":2007,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Genomics and Phylogenetic Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":354,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Human Genome Research Institute; RIKEN; Hospital for Sick Children; Vedecká Grantová Agentúra MŠVVaŠ SR a SAV; Wellcome Trust","keywords":"Annotation; Biology; Zebrafish; Genome; Human genome; Sanger sequencing; Genome project; Database; Danio; Genetics; Genomics; Vertebrate; Haplotype; Computational biology; Vega; Gene; DNA sequencing; Genotype; Computer science","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001072979,0.00225149,0.00300527,0.0103519,0.00185279,0.002265006,0.00286993,0.001461875,0.03149447],"category_scores_gemma":[0.002064925,0.001060874,0.001668425,0.00964623,0.0004113839,0.001082403,0.001991514,0.001697902,0.02323978],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008087874,"about_ca_system_score_gemma":0.001892866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007538842,"about_ca_topic_score_gemma":0.009086153,"domain_scores_codex":[0.9991952,0.0001748965,0.0001154017,0.0002341888,0.0001690954,0.0001112376],"domain_scores_gemma":[0.9993855,0.000124478,0.0001147535,0.0001425193,0.0001431404,0.0000897307],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001150209,0.0001044466,0.003909765,0.01281721,0.0008506746,0.001040494,0.0007089219,0.003543851,0.07600993,0.0135896,0.7567779,0.129497],"study_design_scores_gemma":[0.0001160862,0.00009143943,0.007553703,0.000792669,0.0003872517,0.0007489875,0.00009969789,0.001917309,0.00482277,0.004293097,0.9790599,0.0001171091],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.01108324,0.01685249,0.04742121,0.0006423575,0.0006421529,0.0004646388,0.8766136,0.02422526,0.02205511],"genre_scores_gemma":[0.009118391,0.004772451,0.04508755,0.0001639312,0.00004414105,0.0005779002,0.9344894,0.001745074,0.004001156],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.03149447,"threshold_uncertainty_score":0.1053595,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04034577712481557,"score_gpt":0.3380113653467654,"score_spread":0.2976655882219498,"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."}}