{"id":"W4313033418","doi":"10.33965/mccsis2022_202206c031","title":"CLASSIFIER RANK - A NEW CLASSIFICATION ASSESSMENT METHOD","year":2022,"lang":"en","type":"article","venue":"","topic":"Imbalanced Data Classification Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University","funders":"","keywords":"Classifier (UML); Confusion matrix; Computer science; Artificial intelligence; Confusion; Pattern recognition (psychology); Machine learning; Quadratic classifier; Margin classifier; Multiclass classification; Support vector machine","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":[0.007614757,0.001805362,0.002379709,0.01001935,0.001486993,0.004334277,0.002294744,0.001781424,0.003528108],"category_scores_gemma":[0.0236324,0.0003591072,0.0009800046,0.00418899,0.0009026513,0.004520419,0.001694633,0.002053538,0.003113392],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00141505,"about_ca_system_score_gemma":0.00252683,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002190887,"about_ca_topic_score_gemma":0.002394849,"domain_scores_codex":[0.9834185,0.002932138,0.00121961,0.00168058,0.01020787,0.0005413543],"domain_scores_gemma":[0.9801854,0.005927356,0.001761498,0.001379799,0.01026646,0.0004794951],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002876897,0.0002471415,0.01048051,0.00050347,0.000323782,0.0001349672,0.0001463983,0.02183721,0.009498193,0.01897992,0.03408403,0.9034767],"study_design_scores_gemma":[0.00009057549,0.0005189221,0.005273499,0.0001230326,0.000230242,0.0008136478,0.000138089,0.9184336,0.01532895,0.02864247,0.03019834,0.000208565],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01375808,0.002550553,0.971982,0.0006415441,0.0005587062,0.0004139849,0.001072026,0.00389618,0.005126881],"genre_scores_gemma":[0.3312567,0.001575239,0.6494583,0.0006378972,0.001600255,0.0009694362,0.003897379,0.0006094329,0.00999532],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.01001935,"threshold_uncertainty_score":0.04027116,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05124846867724971,"score_gpt":0.3561920089092239,"score_spread":0.3049435402319742,"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."}}