{"id":"W2155039816","doi":"10.1109/ccece.2014.6901122","title":"Model verification of GMM clustering based on signature testing","year":2014,"lang":"en","type":"article","venue":"","topic":"Bayesian Methods and Mixture Models","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Cluster analysis; Mixture model; Computer science; Signature (topology); Robustness (evolution); Pattern recognition (psychology); Data mining; Statistic; Data modeling; Artificial intelligence; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"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":[0.0004402718,0.00007349511,0.00009579139,0.00005601965,0.00003788886,0.00002680088,0.0003428757,0.00005561635,0.000002123311],"category_scores_gemma":[0.0001047241,0.00005970545,0.00002851433,0.0001733265,0.00001046599,0.0001088439,0.00004582468,0.00008646777,0.00000242279],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000932093,"about_ca_system_score_gemma":0.00002516082,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005119337,"about_ca_topic_score_gemma":0.000001763289,"domain_scores_codex":[0.9993462,0.00006065672,0.0001279804,0.0002166876,0.0001375074,0.0001109752],"domain_scores_gemma":[0.9992384,0.0001552646,0.00006230314,0.0004413246,0.00006443125,0.00003831454],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007358612,0.00005659335,0.0000430644,0.00004240275,0.000002710925,4.743578e-7,0.0001635641,0.2436723,0.08638907,0.2989211,0.0002061148,0.3704953],"study_design_scores_gemma":[0.0001073736,0.00004790695,0.0001067524,0.00002257739,0.000001488835,4.716132e-7,4.684504e-7,0.9760803,0.008792371,0.0147383,0.00003100063,0.00007102031],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0003847264,0.000004123687,0.9708037,0.0002746978,0.00005962642,0.00005791572,2.999599e-7,0.00008275537,0.0283321],"genre_scores_gemma":[0.4753902,9.677982e-8,0.5241448,0.0003693934,0.00001245294,0.000001825041,2.548537e-7,0.000002905999,0.0000781524],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.732408,"threshold_uncertainty_score":0.2434718,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03980318581963228,"score_gpt":0.2653103332773539,"score_spread":0.2255071474577217,"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."}}