{"id":"W3179186621","doi":"10.1109/memea52024.2021.9478696","title":"Biological Data Classification via Faster MAXimum Feasible Subsystem Algorithm","year":2021,"lang":"en","type":"article","venue":"","topic":"Machine Learning and Data Classification","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Hyperparameter; Computer science; Naive Bayes classifier; Support vector machine; Machine learning; Artificial intelligence; Statistical classification; Algorithm; Precision and recall; Logistic regression; Data mining","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":[0.002647957,0.001177887,0.00165195,0.002326381,0.0005788468,0.00136394,0.001813616,0.001264076,0.003882883],"category_scores_gemma":[0.007158273,0.000516123,0.001404124,0.002271559,0.0005441175,0.001575531,0.001281129,0.001188181,0.001713886],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007488304,"about_ca_system_score_gemma":0.001820106,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004237265,"about_ca_topic_score_gemma":0.003164181,"domain_scores_codex":[0.9984445,0.0004858725,0.0001534975,0.0003287577,0.0004887267,0.00009863736],"domain_scores_gemma":[0.9978326,0.001055012,0.0001925286,0.0003531542,0.0005152668,0.00005136342],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005168331,0.0001683142,0.003472712,0.0002315357,0.00016731,0.0001345029,0.0001960852,0.2573463,0.01618607,0.009073654,0.004622388,0.7078843],"study_design_scores_gemma":[0.00002415643,0.00006425603,0.0005410725,0.000008514566,0.00001433396,0.00004397856,0.00001865853,0.9915262,0.002263471,0.004245595,0.001241612,0.000008104937],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01654116,0.0002781023,0.9808515,0.0001443073,0.00002364803,0.0000744936,0.0001107169,0.001383953,0.0005920822],"genre_scores_gemma":[0.1856767,0.0002140462,0.8097069,0.0001354887,0.00005578822,0.000362844,0.001496366,0.0001654703,0.002186376],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.004237265,"threshold_uncertainty_score":0.01400387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1192339268067348,"score_gpt":0.3128357248205287,"score_spread":0.1936017980137938,"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."}}