{"id":"W2942409680","doi":"10.1080/15476286.2019.1600395","title":"Circbank: a comprehensive database for circRNA with standard nomenclature","year":2019,"lang":"en","type":"article","venue":"RNA Biology","topic":"Circular RNAs in diseases","field":"Biochemistry, Genetics and Molecular Biology","cited_by":619,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Biology; Computational biology; Gene; Circular RNA; Gene nomenclature; RNA splicing; Genetics; microRNA; Database; RNA; Nomenclature; Computer science","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":[0.002672001,0.002016191,0.002814495,0.009482111,0.001452608,0.004026335,0.002503292,0.002066119,0.04427195],"category_scores_gemma":[0.007343994,0.001078,0.001167203,0.008745339,0.0005784478,0.002466083,0.00317314,0.002230922,0.05460609],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007810847,"about_ca_system_score_gemma":0.003863134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001395518,"about_ca_topic_score_gemma":0.001392966,"domain_scores_codex":[0.9982885,0.0002674719,0.0004769676,0.0004150813,0.0004049917,0.0001470521],"domain_scores_gemma":[0.9961485,0.001214031,0.0008868638,0.0006231737,0.0006063791,0.0005211903],"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":[0.001491728,0.0001268493,0.002669597,0.01244811,0.0003065383,0.0009443532,0.0004196545,0.0007758087,0.04853943,0.0159199,0.8119168,0.1044412],"study_design_scores_gemma":[0.0001689451,0.00008583868,0.002444497,0.000680713,0.000179771,0.0008635433,0.00006561883,0.0008323696,0.007335874,0.004459441,0.9827979,0.00008564359],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.005685787,0.01301812,0.05388993,0.0007522852,0.001382957,0.0005811098,0.8585369,0.04426588,0.02188692],"genre_scores_gemma":[0.004709081,0.003851931,0.03823669,0.0004408091,0.0002526253,0.0005789233,0.9431587,0.004076255,0.004695097],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.04427195,"threshold_uncertainty_score":0.1481044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009719516369764314,"score_gpt":0.2683765597683567,"score_spread":0.2586570433985924,"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."}}