{"id":"W3205092057","doi":"10.1002/cjs.11651","title":"Testing homogeneity in contaminated mixture models","year":2021,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"York University","funders":"National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Homogeneity (statistics); Limiting; Computer science; Null hypothesis; Mathematics; Biological system; Statistics; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.03079195,0.00118617,0.002041807,0.003524313,0.001241547,0.002630474,0.003225287,0.002770441,0.003397868],"category_scores_gemma":[0.1848693,0.001085446,0.002424883,0.002301145,0.004828977,0.004217166,0.005623091,0.002719733,0.0007704807],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001275327,"about_ca_system_score_gemma":0.001843216,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003222494,"about_ca_topic_score_gemma":0.0014622,"domain_scores_codex":[0.9624322,0.0273932,0.001443751,0.003772025,0.003817506,0.00114122],"domain_scores_gemma":[0.8060129,0.174012,0.005571428,0.007973795,0.005206765,0.001223082],"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":[0.001895023,0.0003292393,0.06485355,0.0007111325,0.001973958,0.001596166,0.001678254,0.2952094,0.007552073,0.4421099,0.004060307,0.178031],"study_design_scores_gemma":[0.0001468493,0.0002985438,0.009956587,0.0001302083,0.0001767738,0.0006003671,0.0003039225,0.6473783,0.003829949,0.3340585,0.002982949,0.0001370379],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.06059474,0.0003976669,0.9365945,0.0003823922,0.00005076392,0.00008193386,0.0002147289,0.0003613999,0.00132191],"genre_scores_gemma":[0.8191605,0.0004449751,0.1760749,0.0004786979,0.0002071169,0.0003906451,0.001517131,0.0002334098,0.001492687],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03079195,"threshold_uncertainty_score":0.1628454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0360547725776767,"score_gpt":0.2493521132847954,"score_spread":0.2132973407071187,"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."}}