{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003162894,0.001078822,0.001605351,0.001669479,0.0007975856,0.001318341,0.002016327,0.001285795,0.001591387],"category_scores_gemma":[0.01717439,0.0004605651,0.001111613,0.001230609,0.001389852,0.002517804,0.002424597,0.00156822,0.001043868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001051309,"about_ca_system_score_gemma":0.002027461,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00353216,"about_ca_topic_score_gemma":0.002239877,"domain_scores_codex":[0.9962785,0.001179139,0.0001962654,0.0007399868,0.001348432,0.0002575904],"domain_scores_gemma":[0.9948056,0.0020268,0.0006332511,0.001070474,0.001310554,0.0001533338],"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":[0.0008788526,0.0001303322,0.007452525,0.0002092121,0.0002191767,0.0003306951,0.0003834375,0.348956,0.0380105,0.05230329,0.002729997,0.5483961],"study_design_scores_gemma":[0.00001072842,0.0000534115,0.0007234744,0.000008329553,0.00001655522,0.0001385348,0.00003444913,0.9754711,0.01262038,0.0100566,0.0008322113,0.00003410826],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.01778959,0.00009417786,0.9803585,0.00007303644,0.00004124454,0.00002503546,0.00004281092,0.0008945852,0.0006810476],"genre_scores_gemma":[0.6701878,0.0001934882,0.3270785,0.000132249,0.00006539271,0.0001159749,0.0003766473,0.0003388211,0.001511037],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.00353216,"threshold_uncertainty_score":0.01672715,"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."}}