{"id":"W2413627438","doi":"","title":"Appendices to Applied Regression Analysis, Generalized Linear Models, and Related Methods, Second Edition","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"","keywords":"Linear regression; Regression analysis; Statistics; Mathematics; Econometrics; Computer science","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001042614,0.0001975139,0.000477729,0.0001909538,0.0001277025,0.000030379,0.0001103055,0.0001793347,0.001245956],"category_scores_gemma":[0.0003426941,0.000142033,0.00007945763,0.0003572678,0.0000512647,0.0001308147,0.00009284492,0.0002994366,0.000008994744],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009457333,"about_ca_system_score_gemma":0.00001223908,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000008998535,"about_ca_topic_score_gemma":0.00007157454,"domain_scores_codex":[0.9985567,0.0001472815,0.0004273676,0.0004431907,0.0001839402,0.0002415504],"domain_scores_gemma":[0.9984131,0.0007642411,0.0001381443,0.0003685602,0.00007148142,0.0002445025],"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":[0.00005258756,0.00005405879,0.000004301548,0.00004015701,0.0001728957,0.000002709266,0.000316528,0.0003668067,0.0572737,0.9107468,0.0009001314,0.03006938],"study_design_scores_gemma":[0.0003686491,0.00002341108,0.00002817572,0.000007397669,0.0002799062,0.000003792807,0.00006300634,0.1299083,0.008375883,0.859419,0.001313521,0.0002089478],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02156263,0.00002496862,0.966037,0.0001288404,0.000161766,0.0003139393,0.00003062113,0.0001233784,0.01161687],"genre_scores_gemma":[0.05169969,0.00001389305,0.9461899,0.0001208003,0.00007583623,0.00003785211,0.0000339178,0.00002583589,0.001802246],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.1295415,"threshold_uncertainty_score":0.999667,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08560811182933221,"score_gpt":0.4537168547098716,"score_spread":0.3681087428805394,"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."}}