{"id":"W2110162240","doi":"10.2307/3315900","title":"A fast distance‐based approach for determining the number of components in mixtures","year":2003,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Bayes' theorem; Bayesian probability; Algorithm; Software; Mathematics; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005680498,0.00008569883,0.0001974326,0.00009171281,0.00007119278,0.00005406204,0.0004264999,0.00003678183,0.000004635338],"category_scores_gemma":[0.0002403004,0.00006300581,0.00004666843,0.0001543861,0.0000751341,0.00007575647,0.000005279843,0.0001419847,1.657507e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005600188,"about_ca_system_score_gemma":0.0006172577,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001516415,"about_ca_topic_score_gemma":0.0007241372,"domain_scores_codex":[0.9990932,0.0001281076,0.0003345125,0.00009443699,0.0001283732,0.0002213408],"domain_scores_gemma":[0.9989585,0.0002591037,0.0002308173,0.0001639804,0.0001948589,0.0001927622],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001958003,0.000081558,0.0293286,0.0001175513,0.00003870654,0.00008774111,0.001956537,0.001120335,0.00008404112,0.9032962,0.003682413,0.06018678],"study_design_scores_gemma":[0.00757605,0.0004817232,0.05042645,0.000410997,0.0001356672,0.0003848287,0.0002843877,0.4896733,0.001720937,0.4284316,0.01937523,0.001098843],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.001415989,0.00007521815,0.9974861,0.0000602213,0.0001856578,0.00009821315,0.00008649067,0.000001071551,0.0005910923],"genre_scores_gemma":[0.4226462,0.000001041211,0.5772114,0.0001093941,0.00001198168,0.00000157795,0.000001489738,0.000004555156,0.00001238291],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.488553,"threshold_uncertainty_score":0.2569302,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04590796759457682,"score_gpt":0.2777227591141974,"score_spread":0.2318147915196205,"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."}}