{"id":"W187143880","doi":"10.22237/jmasm/1209614580","title":"On Measuring the Relative Importance of Explanatory Variables in a Logistic Regression","year":2008,"lang":"en","type":"article","venue":"Journal of Modern Applied Statistical Methods","topic":"Sensory Analysis and Statistical Methods","field":"Agricultural and Biological Sciences","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ontario Tech University; St. Francis Xavier University; University of British Columbia; Carleton University","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada; Mitacs","keywords":"Logistic regression; Mathematics; Statistics; Econometrics; Variables; Regression analysis; Binomial regression; Linear regression; Variable (mathematics); Logit","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":[0.003458286,0.0001787667,0.0006365851,0.00004473795,0.0001467758,0.00001211585,0.0003000771,0.0001119302,0.0002179156],"category_scores_gemma":[0.00421589,0.00005769578,0.0001236703,0.0003433394,0.000276972,0.00005438925,0.00003979015,0.0005518286,0.000001647279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000528191,"about_ca_system_score_gemma":0.00002846652,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001326803,"about_ca_topic_score_gemma":0.0000118366,"domain_scores_codex":[0.9967004,0.001354779,0.0009367723,0.0002355835,0.0005248556,0.0002476208],"domain_scores_gemma":[0.9836168,0.01542582,0.0005965083,0.00009858864,0.0001324145,0.0001298548],"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":[0.001378512,0.0005044665,0.002828633,0.00003327647,0.0001495523,0.0002535759,0.0005250313,0.001289645,0.1221213,0.4534031,0.0004035065,0.4171094],"study_design_scores_gemma":[0.0004979279,0.00052011,0.111272,0.0001209754,0.000102009,0.00007681069,0.0002223632,0.01247234,0.002762412,0.8714868,0.0002247058,0.0002415167],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1157367,0.0003047778,0.8813112,0.0002525977,0.00008537377,0.0001309364,0.00003994426,0.000006991726,0.002131389],"genre_scores_gemma":[0.6773457,0.00004944361,0.3224154,0.0001054877,0.00005369666,0.000004303065,0.000002183438,0.000001690414,0.0000221582],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.561609,"threshold_uncertainty_score":0.5047118,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1394103675032325,"score_gpt":0.3638800808284937,"score_spread":0.2244697133252612,"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."}}