{"id":"W2942651266","doi":"10.1111/bmsp.12166","title":"Bayesian generalized structured component analysis","year":2019,"lang":"en","type":"article","venue":"British Journal of Mathematical and Statistical Psychology","topic":"Advanced Statistical Methods and Models","field":"Mathematics","cited_by":13,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National University of Singapore","keywords":"Component (thermodynamics); Bayesian probability; Component analysis; Econometrics; Mathematics; Statistics; Computer science; Applied mathematics","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":[0.0009310232,0.0002047494,0.001211902,0.0001525945,0.00006854827,0.00006277856,0.0002035965,0.0001506436,0.003235145],"category_scores_gemma":[0.001438272,0.0001770343,0.0001971559,0.0002197104,0.0002509925,0.00008478045,0.00005283467,0.0004543182,0.00001451467],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001565356,"about_ca_system_score_gemma":0.00001973149,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003690516,"about_ca_topic_score_gemma":0.000005560431,"domain_scores_codex":[0.9973703,0.0003995725,0.001138173,0.0003206944,0.00040035,0.0003709252],"domain_scores_gemma":[0.9964494,0.002419228,0.0003545098,0.0002197742,0.0001803975,0.0003766739],"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":[0.0001970107,0.000362774,0.0001652248,0.0001967384,0.0006717607,0.0004906046,0.00009102751,0.00002067256,0.0004203444,0.9432666,0.0018945,0.05222278],"study_design_scores_gemma":[0.001433004,0.0002878605,0.003135748,0.00006588927,0.0006000849,0.002018759,0.0000428908,0.005331385,0.00001208389,0.9865221,0.0003390686,0.0002110661],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06421437,0.0002291589,0.9331979,0.0002214032,0.0001584577,0.000175029,0.0001167733,0.00001634373,0.001670571],"genre_scores_gemma":[0.3263868,0.00008708128,0.6730499,0.0002534867,0.00005499025,0.000002773465,0.000005215849,0.0000204632,0.0001392451],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.2621725,"threshold_uncertainty_score":0.997676,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0576921882517152,"score_gpt":0.4172079433688679,"score_spread":0.3595157551171527,"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."}}