{"id":"W2924551033","doi":"10.21037/atm.2019.01.70","title":"Orphan noncoding RNAs: novel regulators and cancer biomarkers","year":2019,"lang":"en","type":"letter","venue":"Annals of Translational Medicine","topic":"Cancer-related molecular mechanisms research","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Institute for Cancer Research; University of Toronto; University Health Network; Princess Margaret Cancer Centre","funders":"Canadian Institutes of Health Research; University of Toronto; Princess Margaret Cancer Foundation","keywords":"Biology; Computational biology; Gene; Reprogramming; microRNA; Non-coding RNA; Long non-coding RNA; Genome; Genetics; Regulation of gene expression; Human genome; Cancer; RNA; Bioinformatics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.000756678,0.0005281226,0.0006817026,0.0004414704,0.0006001033,0.001273655,0.0006358075,0.00487249,0.003811958],"category_scores_gemma":[0.002035576,0.0002280894,0.0003536034,0.0003655014,0.002107652,0.002000018,0.0005427783,0.005619383,0.002814758],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00130327,"about_ca_system_score_gemma":0.0004823913,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001644838,"about_ca_topic_score_gemma":0.0003515795,"domain_scores_codex":[0.9995813,0.0001169854,0.00003335375,0.00008694041,0.0001341687,0.00004721957],"domain_scores_gemma":[0.9989032,0.0006331026,0.0001312952,0.00005074529,0.0001444507,0.000137232],"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":[0.0007903362,0.0001560958,0.004977976,0.001301323,0.00007446955,0.02351522,0.0003265338,0.0004336893,0.02098187,0.06375237,0.4840774,0.3996127],"study_design_scores_gemma":[0.0001253811,0.0002177882,0.001558339,0.0004508667,0.00005611188,0.02287556,0.0002458385,0.0008658865,0.004144907,0.04302331,0.9263938,0.00004219058],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.007044562,0.2352909,0.003718852,0.7020135,0.03486214,0.00005792983,0.0001657965,0.0001421524,0.01670414],"genre_scores_gemma":[0.1054158,0.2472653,0.006265445,0.3936916,0.2119654,0.000190643,0.0002179965,0.00007795761,0.03490986],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.00487249,"threshold_uncertainty_score":0.01275223,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0564669379339523,"score_gpt":0.3514555966280417,"score_spread":0.2949886586940894,"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."}}