{"id":"W4401160419","doi":"10.1080/07362994.2024.2372605","title":"Mixtures of multivariate Gaussians","year":2024,"lang":"en","type":"article","venue":"Stochastic Analysis and Applications","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Australian Research Council; Natural Sciences and Engineering Research Council of Canada","keywords":"Mathematics; Multivariate statistics; Econometrics; Mixture model; Statistics; Applied mathematics","routes":{"ca_aff":true,"ca_fund":true,"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":[0.003252386,0.001297422,0.001817166,0.002365403,0.0007362517,0.003265915,0.001935348,0.001945821,0.003895527],"category_scores_gemma":[0.01281099,0.0009197706,0.001828271,0.003038086,0.002400068,0.004784967,0.002287119,0.003357973,0.001584675],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001080916,"about_ca_system_score_gemma":0.0007696662,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003514735,"about_ca_topic_score_gemma":0.002617586,"domain_scores_codex":[0.9970783,0.0011234,0.0001152466,0.0006491388,0.0008380388,0.0001957508],"domain_scores_gemma":[0.9967557,0.002152015,0.0003132304,0.0003696998,0.0003204845,0.00008890388],"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":[0.0000506846,0.00002439483,0.001133948,0.0001578157,0.0001070204,0.0001248255,0.0002501235,0.09531578,0.001245077,0.8510576,0.002332614,0.04820023],"study_design_scores_gemma":[0.00001071054,0.00002966021,0.0008017462,0.00007995337,0.00005081477,0.0002744503,0.00005555115,0.5267751,0.000605253,0.4579397,0.01332133,0.00005582716],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.003388576,0.001759833,0.9908475,0.0003218432,0.0001245296,0.00001944021,0.000111818,0.0002170719,0.003209314],"genre_scores_gemma":[0.4406186,0.01462646,0.5161725,0.0008269634,0.001578034,0.0002682758,0.001044969,0.0003835501,0.02448072],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003895527,"threshold_uncertainty_score":0.01720047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009958612752616764,"score_gpt":0.2882501070217248,"score_spread":0.278291494269108,"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."}}