{"id":"W7154625270","doi":"10.66573/001c.137029","title":"Linear Classifier Models for Binary Classification","year":2025,"lang":"en","type":"article","venue":"Variance","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Weighting; Classifier (UML); Binary classification; Pattern recognition (psychology); Linear classifier; Parametric statistics; Logistic regression; Binary number; A-weighting","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":[0.0003369455,0.0001336382,0.0001496955,0.0001691742,0.0001658458,0.0001076998,0.00118995,0.0001210231,0.000003967097],"category_scores_gemma":[0.00009762921,0.0001354413,0.00005807914,0.0006793286,0.0000483335,0.0009182194,0.0001526634,0.0001172355,0.00003193961],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008877536,"about_ca_system_score_gemma":0.0001747498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004351918,"about_ca_topic_score_gemma":9.647449e-7,"domain_scores_codex":[0.9987242,0.00004522399,0.0002918282,0.0005475428,0.0001434507,0.0002477521],"domain_scores_gemma":[0.9982725,0.0001455901,0.0001224258,0.001209529,0.0002065776,0.00004336469],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008228545,0.0000491301,0.00002402882,0.00002363115,0.000008403279,4.231891e-7,0.00003307625,0.0001349048,0.008308519,0.9470665,0.02610747,0.01823565],"study_design_scores_gemma":[0.000217034,0.00002505011,0.00118334,0.00003242191,0.000004807389,8.321151e-7,0.000006016766,0.7652161,0.005380664,0.1301084,0.09769076,0.0001345729],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.00004192505,0.00009263163,0.9803717,0.006956239,0.0004157122,0.000465041,0.00002495779,0.0006485996,0.01098325],"genre_scores_gemma":[0.2135929,0.00007129244,0.7775628,0.001758154,0.00008028163,0.0006067151,0.00005208535,0.00001447889,0.00626127],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.8169581,"threshold_uncertainty_score":0.5523137,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05282643759995619,"score_gpt":0.3130133274218485,"score_spread":0.2601868898218923,"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."}}