{"id":"W4285012250","doi":"10.1080/00949655.2022.2093873","title":"Robust ranking by ensembling of diverse models and assessment metrics","year":2022,"lang":"en","type":"article","venue":"Journal of Statistical Computation and Simulation","topic":"Machine Learning in Bioinformatics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Thompson Rivers University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Feature selection; Classifier (UML); Artificial intelligence; Pattern recognition (psychology); Mathematics; Machine learning; Feature (linguistics); Ranking (information retrieval); Data mining; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003992235,0.00004946138,0.000104448,0.00007828187,0.00009459428,0.0000188224,0.0000303664,0.00002319978,0.000008790783],"category_scores_gemma":[0.0001247668,0.00004794213,0.00001707215,0.00006692982,0.00002509875,0.00001115719,0.00005746557,0.0001218924,2.713939e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001391943,"about_ca_system_score_gemma":0.0000259547,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002757231,"about_ca_topic_score_gemma":1.931718e-7,"domain_scores_codex":[0.9992828,0.0000871425,0.0002994445,0.00005740334,0.0002223517,0.00005082889],"domain_scores_gemma":[0.9993609,0.0001637294,0.0002842905,0.00002631363,0.0001269517,0.00003780699],"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":[0.00005179381,0.00002391893,0.0009869586,0.0000233521,0.000018551,8.561145e-7,0.0001278647,0.9809622,0.0007398457,0.0007173702,0.0001364092,0.01621088],"study_design_scores_gemma":[0.0006178481,0.0003505232,0.001572521,0.000004587048,0.00002334389,0.00001306297,0.0001979053,0.9957507,0.00003525386,0.001053093,0.0003323887,0.00004883201],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2599658,0.0001163191,0.7397175,0.00002457978,0.00003421088,0.00003588528,0.0000183572,0.000001110794,0.00008624462],"genre_scores_gemma":[0.910835,0.00003480159,0.08901215,0.00004443485,0.00001537571,2.946728e-7,0.00004823256,0.000003932791,0.000005798585],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6508692,"threshold_uncertainty_score":0.1955023,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03701339128923762,"score_gpt":0.332139746488871,"score_spread":0.2951263551996333,"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."}}