{"id":"W3039979742","doi":"10.1002/cjs.11557","title":"Homogeneity testing under finite location‐scale mixtures","year":2020,"lang":"en","type":"article","venue":"Canadian Journal of Statistics","topic":"Statistical Distribution Estimation and Applications","field":"Mathematics","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; University of British Columbia","funders":"National Natural Science Foundation of China; Natural Science Foundation of Shanghai","keywords":"Homogeneity (statistics); Univariate; Ratio test; Limiting; Likelihood-ratio test; Mathematics; Applied mathematics; Scale (ratio); Statistical hypothesis testing; Statistics; Computer science; Statistical physics; Multivariate statistics; Engineering; Physics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001514876,0.0001074263,0.0001892375,0.00006578249,0.0001903492,0.0000677034,0.0001867531,0.00005088678,0.0004239562],"category_scores_gemma":[0.006664326,0.000106134,0.00003193797,0.0003980634,0.0001258291,0.0000634045,0.000007953221,0.0002030943,0.00005908657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009030121,"about_ca_system_score_gemma":0.0009776561,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002022209,"about_ca_topic_score_gemma":0.0009731642,"domain_scores_codex":[0.9989764,0.00004530249,0.000487097,0.0001011999,0.0001885352,0.0002014281],"domain_scores_gemma":[0.9968097,0.001050015,0.000280752,0.0001086783,0.0009068304,0.0008440799],"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":[0.000008516603,0.00004467829,0.001530158,0.0001322986,0.00005466635,0.000065932,0.0006256755,0.002404494,0.0002069509,0.7478471,0.2409619,0.00611757],"study_design_scores_gemma":[0.001737947,0.0004269014,0.04762077,0.000230892,0.0004795538,0.0002318509,0.001111839,0.08611481,0.001157381,0.8310174,0.02895392,0.0009167307],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001850049,0.00005454418,0.993016,0.002556578,0.00008258686,0.0000873763,0.001553642,0.00001466936,0.0007845454],"genre_scores_gemma":[0.7358956,0.0000021869,0.2628331,0.001039222,0.0001288874,0.000002477929,0.00003992263,0.00001496913,0.00004357119],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.7340456,"threshold_uncertainty_score":0.7978303,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1309173343803162,"score_gpt":0.3172173217490399,"score_spread":0.1862999873687237,"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."}}