{"id":"W4399158654","doi":"10.1007/s00357-024-09473-3","title":"Finding Outliers in Gaussian Model-based Clustering","year":2024,"lang":"en","type":"article","venue":"Journal of Classification","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":false,"ca_institutions":"McMaster University","funders":"Canada Research Chairs","keywords":"Outlier; Cluster analysis; Pattern recognition (psychology); Artificial intelligence; Mathematics; Gaussian; Computer science; Statistics; Physics","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":[0.0107617,0.001418456,0.003818827,0.004752093,0.001857609,0.003607075,0.005235739,0.00410092,0.0009613177],"category_scores_gemma":[0.05216891,0.001907924,0.0019366,0.004068938,0.002791654,0.004112893,0.003558637,0.003760118,0.0006263684],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001877909,"about_ca_system_score_gemma":0.001642167,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009971743,"about_ca_topic_score_gemma":0.008308856,"domain_scores_codex":[0.9917228,0.00338007,0.00056973,0.001401679,0.002461716,0.0004640262],"domain_scores_gemma":[0.9741149,0.01831824,0.00171336,0.002184535,0.0030986,0.000570238],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00113685,0.0003859098,0.01457835,0.0004208816,0.0005692557,0.0002134994,0.0006295023,0.76375,0.004437922,0.03315751,0.00481937,0.175901],"study_design_scores_gemma":[0.00001219804,0.0000244796,0.0005842736,0.00001439493,0.00002059554,0.00003889008,0.00004744069,0.9788902,0.0007428766,0.01928116,0.0003262615,0.00001728951],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.02418827,0.0005519933,0.974342,0.0001649569,0.00005114306,0.00003323692,0.00006016031,0.0003888746,0.0002192951],"genre_scores_gemma":[0.5333211,0.0006136029,0.4623657,0.0001612288,0.0001794051,0.0001573571,0.001080951,0.0004557003,0.001664933],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0107617,"threshold_uncertainty_score":0.05691397,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05584761604273475,"score_gpt":0.3315201195779214,"score_spread":0.2756725035351866,"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."}}