{"id":"W2952713926","doi":"10.1093/bioinformatics/bty244","title":"COSSMO: predicting competitive alternative splice site selection using deep learning","year":2018,"lang":"en","type":"article","venue":"Bioinformatics","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":66,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Genomics; University of Toronto","funders":"","keywords":"splice; Computer science; RNA splicing; Sequence (biology); Alternative splicing; Computational biology; Selection (genetic algorithm); Artificial intelligence; Data mining; Gene; Biology; Genetics; RNA","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0006815013,0.0009800812,0.0005294774,0.0004703545,0.0003050647,0.000516724,0.001273965,0.0009319871,0.001864663],"category_scores_gemma":[0.00145608,0.0003484309,0.0005235047,0.0005616656,0.000393684,0.00072925,0.0006184092,0.001233119,0.0007528907],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008113324,"about_ca_system_score_gemma":0.0009747963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008503946,"about_ca_topic_score_gemma":0.01701364,"domain_scores_codex":[0.9997961,0.00003673787,0.000009783672,0.00007518515,0.00004797485,0.00003423929],"domain_scores_gemma":[0.9995103,0.0002423105,0.00005212182,0.00005069049,0.0001010604,0.00004359255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005484579,0.0003112355,0.02772311,0.000222667,0.000188643,0.000201526,0.00006541968,0.7972596,0.02663384,0.00665379,0.01783967,0.122352],"study_design_scores_gemma":[0.00001298323,0.00001723341,0.0005719092,0.000003923183,0.000006618082,0.00001893836,0.000004028544,0.9941579,0.002503009,0.002233658,0.0004649108,0.000004875003],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4703307,0.001549896,0.503876,0.0009271555,0.0001711201,0.0001202597,0.008440958,0.0087363,0.005847597],"genre_scores_gemma":[0.8647924,0.0003721825,0.1134863,0.0005149234,0.0000737962,0.00018565,0.01479914,0.0003307237,0.00544485],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.008503946,"threshold_uncertainty_score":0.01690888,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01461999723287225,"score_gpt":0.2846627027470284,"score_spread":0.2700427055141561,"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."}}