{"id":"W2912093348","doi":"","title":"Proceedings of the 9th IAPR International Conference on Pattern Recognition in Bioinformatics - Volume 8626","year":2014,"lang":"en","type":"article","venue":"","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Windsor","funders":"","keywords":"Volume (thermodynamics); Computer science; Data 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":[0.004485162,0.001696565,0.003174214,0.003037265,0.001049856,0.005079519,0.00204188,0.001790661,0.05437651],"category_scores_gemma":[0.006752597,0.0005562673,0.001311803,0.002744471,0.001091528,0.002621678,0.00247616,0.003455477,0.04937265],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008948581,"about_ca_system_score_gemma":0.002172212,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00403307,"about_ca_topic_score_gemma":0.004330252,"domain_scores_codex":[0.9975086,0.00078182,0.0001886109,0.0004227747,0.0009217333,0.0001764204],"domain_scores_gemma":[0.9926985,0.001321861,0.000185872,0.001018254,0.003828056,0.0009474945],"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":[0.0003312334,0.0004733821,0.001310357,0.0004123969,0.0001673272,0.0001724931,0.0001033706,0.002182345,0.006431519,0.003789219,0.5170558,0.4675706],"study_design_scores_gemma":[0.0001047176,0.0004778459,0.005983978,0.0006693801,0.0002853342,0.001363283,0.0003152891,0.05710247,0.0114853,0.0201363,0.9019809,0.00009524326],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.02288082,0.06241077,0.6517197,0.02518385,0.07532477,0.001411688,0.006277109,0.01562895,0.1391623],"genre_scores_gemma":[0.06320998,0.04101399,0.3501635,0.005659614,0.01522024,0.0008365643,0.03111378,0.004982808,0.4877995],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.05437651,"threshold_uncertainty_score":0.1819075,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01197928623121896,"score_gpt":0.2384712719333201,"score_spread":0.2264919857021011,"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."}}