{"id":"W2791145377","doi":"10.1080/10705511.2017.1409074","title":"Model Specification Searches in Structural Equation Modeling with <i>R</i>","year":2018,"lang":"en","type":"article","venue":"Structural Equation Modeling A Multidisciplinary Journal","topic":"Bayesian Modeling and Causal Inference","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"","keywords":"Tabu search; Computer science; Simulated annealing; Code (set theory); Structural equation modeling; Programming language; Genetic programming; Ant colony optimization algorithms; Source code; Algorithm; Theoretical computer science; Mathematical optimization; Mathematics; Artificial intelligence; Machine learning","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":[0.01744122,0.002847718,0.001123483,0.002733784,0.0008291103,0.001802446,0.002164064,0.001350737,0.02389378],"category_scores_gemma":[0.09047329,0.0015806,0.002563748,0.003258572,0.001483857,0.00183028,0.00237889,0.002562662,0.01041878],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008691049,"about_ca_system_score_gemma":0.003090137,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003943033,"about_ca_topic_score_gemma":0.006327372,"domain_scores_codex":[0.9845517,0.01234416,0.0007654796,0.0008325459,0.001333942,0.0001722213],"domain_scores_gemma":[0.9399099,0.05310042,0.002264709,0.002830939,0.001676708,0.0002175103],"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":[0.0003980732,0.0002762832,0.007287131,0.002765139,0.001076774,0.0007899684,0.00180912,0.09399361,0.003155013,0.3123129,0.114722,0.461414],"study_design_scores_gemma":[0.0003576445,0.000275875,0.003010364,0.0009419945,0.0003019554,0.0009208005,0.000397893,0.5151125,0.009654541,0.3691282,0.0996834,0.0002148483],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001145646,0.0001556252,0.9906494,0.0003576512,0.00003849446,0.0001433236,0.0006805143,0.00513471,0.001694632],"genre_scores_gemma":[0.01249707,0.0001553647,0.9834606,0.0001273542,0.00001949042,0.001017095,0.0006403577,0.001431963,0.0006507226],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.02389378,"threshold_uncertainty_score":0.09223908,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1252571229299742,"score_gpt":0.3270241969635355,"score_spread":0.2017670740335613,"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."}}