{"id":"W2989698997","doi":"10.1002/cjs.11524","title":"Partial order relations for classification comparisons","year":2019,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Outlier; Constant false alarm rate; Naive Bayes classifier; Classifier (UML); Word error rate; Bayes' theorem; Artificial intelligence; Mathematics; Machine learning; Bayes error rate; Lemma (botany); Computer science; Bayes classifier; Pattern recognition (psychology); Statistics; Data mining; Bayesian probability; Support vector machine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.04681005,0.001661757,0.002184991,0.006319201,0.001918501,0.005837954,0.00203552,0.001798124,0.008788583],"category_scores_gemma":[0.1326796,0.0008872616,0.002696812,0.004824684,0.006318157,0.009792435,0.002726979,0.005271471,0.001695398],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003693015,"about_ca_system_score_gemma":0.003166081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001863401,"about_ca_topic_score_gemma":0.001750583,"domain_scores_codex":[0.9528666,0.03010742,0.00281192,0.00351365,0.009823331,0.0008770698],"domain_scores_gemma":[0.8101836,0.1534357,0.007815496,0.01332803,0.01399578,0.001241345],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001454942,0.00005705383,0.001506575,0.0003103471,0.00009510211,0.00009499659,0.0003378579,0.02253021,0.0008058785,0.89617,0.003587845,0.07435869],"study_design_scores_gemma":[0.00002776203,0.0002108133,0.0008609602,0.0001159462,0.00003641514,0.0001200348,0.00009574854,0.08848724,0.000908936,0.9018968,0.007198609,0.00004074435],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01418451,0.001617836,0.9741045,0.0008797849,0.0002505514,0.0002448884,0.0005980075,0.0002739203,0.007846048],"genre_scores_gemma":[0.2895897,0.001485336,0.6999981,0.000622842,0.0007306496,0.001729654,0.00171354,0.0003313013,0.003798921],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.04681005,"threshold_uncertainty_score":0.2475581,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1947829196111858,"score_gpt":0.410122285163246,"score_spread":0.2153393655520602,"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."}}