{"id":"W6977174215","doi":"10.6084/m9.figshare.15087440","title":"Additional file 3 of InvertypeR: Bayesian inversion genotyping with Strand-seq data","year":2021,"lang":"en","type":"article","venue":"Figshare","topic":"Genomic variations and chromosomal abnormalities","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; BC Cancer Agency","funders":"","keywords":"Bayesian probability; Pattern recognition (psychology); Inversion (geology); Bayes estimator; Bayes' theorem","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00225868,0.002158674,0.001870796,0.003142291,0.001589208,0.00248504,0.003146925,0.001927768,0.763383],"category_scores_gemma":[0.01438431,0.001458526,0.001594519,0.003490927,0.0005451082,0.001629307,0.001735481,0.001949296,0.2403303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001083055,"about_ca_system_score_gemma":0.002108129,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008202979,"about_ca_topic_score_gemma":0.01719326,"domain_scores_codex":[0.9989428,0.0001578426,0.00009856789,0.0003732099,0.0002658999,0.0001616525],"domain_scores_gemma":[0.9886993,0.008383205,0.0004503598,0.001092856,0.0009185667,0.0004557291],"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":[0.0002636363,0.00008566752,0.003049546,0.001618944,0.0001013195,0.000130506,0.0001152244,0.001092967,0.001379128,0.001077009,0.9836595,0.007426636],"study_design_scores_gemma":[0.003017257,0.0001958661,0.02332092,0.00127343,0.000362523,0.0006825934,0.0004146106,0.005078143,0.007053313,0.01640254,0.9418766,0.000322266],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.0002001942,0.00001668586,0.001492688,0.00005172188,0.00003590041,0.00004717125,0.9943601,0.002662269,0.001133277],"genre_scores_gemma":[0.005048541,0.00006876468,0.007839482,0.0004527699,0.00005851519,0.0007781714,0.9738338,0.006845757,0.005074293],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.763383,"threshold_uncertainty_score":0.3375053,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02264666065033287,"score_gpt":0.209268860750276,"score_spread":0.1866222000999432,"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."}}