{"id":"W2005209066","doi":"10.1007/s10182-010-0130-5","title":"Introduction of a new measure for detecting poor fit due to omitted nonlinear terms in SEM","year":2010,"lang":"en","type":"article","venue":"AStA Advances in Statistical Analysis","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":false,"ca_institutions":"Western University","funders":"","keywords":"Heteroscedasticity; Homoscedasticity; Measure (data warehouse); Mathematics; Covariance; Nonlinear system; Covariance matrix; Applied mathematics; Linear model; Residual; Statistics; Econometrics; Computer science; Algorithm","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":[0.0004602228,0.0001247183,0.000372988,0.0003692554,0.00003656654,0.00004792573,0.0003743632,0.00005889555,0.0000323505],"category_scores_gemma":[0.001044467,0.0001145056,0.00006419154,0.001767018,0.00003800719,0.0002944494,0.00007447105,0.0002344521,0.000003918165],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002652029,"about_ca_system_score_gemma":0.00005329161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002325808,"about_ca_topic_score_gemma":0.0060876,"domain_scores_codex":[0.998541,0.00004463828,0.0004428344,0.0004795403,0.0002203436,0.0002716644],"domain_scores_gemma":[0.9990219,0.0003092184,0.0000968415,0.0003267767,0.0001222448,0.0001230065],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009279008,0.0001323867,0.005466439,0.00003767703,0.0000735062,0.00001283329,0.0005929932,0.02789486,0.003817833,0.02013464,0.0001332059,0.9416108],"study_design_scores_gemma":[0.00038614,0.0001423032,0.005575899,0.00002160437,0.00007857678,0.00000407562,0.0000511442,0.964765,0.001577213,0.02608465,0.001077099,0.0002363341],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03997904,0.00003180532,0.9587187,0.0009441179,0.0001230652,0.0001211511,0.00002843069,0.00002400292,0.00002966462],"genre_scores_gemma":[0.5481914,0.000002732738,0.4516356,0.00003861258,0.00008552678,0.00001146886,0.000006459984,0.000003830606,0.00002440724],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9413745,"threshold_uncertainty_score":0.4669402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01631907557253821,"score_gpt":0.3090369573593315,"score_spread":0.2927178817867933,"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."}}