{"id":"W2952619886","doi":"10.1101/474452","title":"Pan-Cancer Repository of Validated Natural and Cryptic mRNA Splicing Mutations","year":2018,"lang":"en","type":"preprint","venue":"bioRxiv (Cold Spring Harbor Laboratory)","topic":"RNA Research and Splicing","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University; Cytodiagnostics (Canada)","funders":"","keywords":"dbSNP; RNA splicing; Genetics; Biology; Computational biology; Gene; Genome; Single-nucleotide polymorphism; Genome browser; Genomics; RNA; Genotype","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":[0.002344576,0.001103488,0.00213084,0.009716754,0.001328501,0.002164094,0.003375749,0.002129183,0.02039147],"category_scores_gemma":[0.006809498,0.0008369827,0.0006905556,0.009327841,0.0004747411,0.0009330456,0.00312087,0.001389231,0.01377064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00122621,"about_ca_system_score_gemma":0.00332557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006200984,"about_ca_topic_score_gemma":0.01170292,"domain_scores_codex":[0.9975826,0.0002309102,0.0002964694,0.0007350799,0.0008743887,0.000280485],"domain_scores_gemma":[0.9932798,0.001532495,0.0006869733,0.002345931,0.001289827,0.000864983],"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":[0.002545585,0.000278573,0.03451564,0.006838815,0.0007664165,0.003226522,0.0004758821,0.003527462,0.06087383,0.005952174,0.7586226,0.1223765],"study_design_scores_gemma":[0.001097015,0.0004949256,0.06629539,0.001403335,0.0009839073,0.007987096,0.0003005387,0.006277421,0.04481145,0.006247988,0.8638307,0.000270279],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0310936,0.006173745,0.00718694,0.0006256633,0.0002538976,0.0002937096,0.932696,0.01097467,0.01070188],"genre_scores_gemma":[0.02479614,0.001147631,0.006911246,0.000329274,0.00006394845,0.0004754791,0.9632366,0.0009022612,0.00213757],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.02039147,"threshold_uncertainty_score":0.06821626,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0109817902157026,"score_gpt":0.25412534734938,"score_spread":0.2431435571336774,"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."}}