{"id":"W2241865608","doi":"","title":"The Variability of Pseudo R2s in Logistic Regression Models","year":2011,"lang":"en","type":"article","venue":"SSRN Electronic Journal","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"","keywords":"Interpretability; Logistic regression; Contrast (vision); Econometrics; Variation (astronomy); Statistics; Regression analysis; Mathematics; Computer science; Artificial intelligence","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00567718,0.0001239972,0.0002525726,0.00004112374,0.0001252213,0.000008009835,0.0002793886,0.00007177487,0.00001520607],"category_scores_gemma":[0.002015061,0.00007110574,0.00007539108,0.0001092485,0.0001253924,0.0001079117,0.00004738832,0.001209279,0.00000106763],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000290493,"about_ca_system_score_gemma":0.0005191066,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002963771,"about_ca_topic_score_gemma":0.0001668406,"domain_scores_codex":[0.9975533,0.0004143851,0.0005083375,0.0001570821,0.0002123151,0.001154511],"domain_scores_gemma":[0.9980237,0.001280586,0.000253424,0.0002814496,0.0001031115,0.00005767977],"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":[0.0001071896,0.00009874479,0.0001019768,0.00001193537,0.00001984039,0.000002127065,0.0002271358,0.00003959275,0.00006851428,0.9698455,0.000007477031,0.02946998],"study_design_scores_gemma":[0.000294761,0.000152811,0.00007663503,0.00004013598,0.0000218847,0.00005087397,0.0003571347,0.007522881,0.0000807731,0.9913107,0.00001010227,0.00008134645],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02123764,0.0003120723,0.9752955,0.00006350791,0.00008325095,0.0001299585,0.000002599165,0.00001083888,0.002864643],"genre_scores_gemma":[0.8747468,0.001104124,0.1238492,0.000008144197,0.00003175269,0.00000655881,1.958589e-7,0.00001597052,0.0002372331],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8535092,"threshold_uncertainty_score":0.5253782,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.144050010518335,"score_gpt":0.4016378676439022,"score_spread":0.2575878571255672,"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."}}