{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0446443,0.002354125,0.003424637,0.007628718,0.001257478,0.004795099,0.004534334,0.005208454,0.003631179],"category_scores_gemma":[0.2366498,0.001385776,0.003105759,0.005911209,0.005164905,0.006654971,0.006415281,0.007131071,0.0006759591],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001406713,"about_ca_system_score_gemma":0.002013274,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009105339,"about_ca_topic_score_gemma":0.00105548,"domain_scores_codex":[0.9596993,0.02520548,0.003389549,0.00509167,0.006205083,0.0004088182],"domain_scores_gemma":[0.6850027,0.2561651,0.0125833,0.02467639,0.01975644,0.001815966],"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":[0.0002239397,0.0003434871,0.0249371,0.001173784,0.001880522,0.0004395437,0.0009873008,0.03905831,0.006647787,0.5255479,0.008772832,0.3899876],"study_design_scores_gemma":[0.0001217129,0.0009026689,0.01561922,0.0004575302,0.0005922439,0.001285684,0.0002458321,0.4622378,0.006981131,0.4945664,0.01654008,0.0004497646],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002259093,0.000248765,0.9958247,0.0004142403,0.0002051071,0.00006093625,0.000131502,0.0002375084,0.0006181517],"genre_scores_gemma":[0.1130249,0.0005556915,0.8815383,0.0009070892,0.001164033,0.0009480004,0.0003989841,0.0003093458,0.001153734],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0446443,"threshold_uncertainty_score":0.2361044,"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."}}