{"id":"W4287328882","doi":"10.48550/arxiv.2102.06851","title":"Robust Model-Based Clustering","year":2021,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Natural Sciences and Engineering Research Council of Canada; Ministry of Defense; Universidad de Buenos Aires","keywords":"Estimator; Cluster analysis; Computer science; Multivariate statistics; Set (abstract data type); Robust statistics; Data mining; Monte Carlo method; Class (philosophy); Algorithm; Mathematics; Artificial intelligence; Statistics; Machine learning","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0065252,0.001767924,0.003193262,0.004898372,0.001305306,0.003714165,0.00636522,0.003391499,0.004256724],"category_scores_gemma":[0.02400977,0.001427671,0.003618488,0.004890499,0.00231689,0.004432953,0.004911517,0.003763126,0.003581664],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001868821,"about_ca_system_score_gemma":0.002575603,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003806562,"about_ca_topic_score_gemma":0.003308631,"domain_scores_codex":[0.9910983,0.003372592,0.0003757018,0.001972459,0.002815601,0.000365256],"domain_scores_gemma":[0.9920073,0.002494429,0.0008442991,0.002807139,0.001651229,0.0001955425],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00009331277,0.0001002657,0.001609575,0.0003713168,0.0005122821,0.0001137683,0.0002776111,0.4194389,0.005804081,0.3383735,0.01264904,0.2206563],"study_design_scores_gemma":[0.00002042492,0.00003060154,0.0003929399,0.00004528217,0.00004578507,0.0001074932,0.00003016403,0.8089315,0.002199508,0.1777467,0.01038888,0.0000606638],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0004875887,0.000123582,0.9985484,0.00006524608,0.0000202756,0.00001642024,0.00006746246,0.0002082211,0.0004627732],"genre_scores_gemma":[0.05109655,0.0006081755,0.9431927,0.0002498662,0.0001675075,0.0002658283,0.001181554,0.0006386274,0.00259917],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0065252,"threshold_uncertainty_score":0.034509,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1260493335254669,"score_gpt":0.2006607022520942,"score_spread":0.0746113687266273,"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."}}