{"id":"W4247582225","doi":"10.32920/ryerson.14648265.v1","title":"k-MACE Clustering for Gaussian Clusters","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Mace; Cluster analysis; Preprocessor; Computer science; Mathematics; Gaussian; Cluster (spacecraft); Algorithm; Covariance; Statistics; Artificial intelligence; Physics; Medicine","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":[0.00484728,0.001457619,0.002008579,0.003024374,0.001968872,0.002461102,0.003555312,0.003042143,0.003627721],"category_scores_gemma":[0.01813734,0.0007844645,0.002015597,0.003104979,0.001605232,0.002946234,0.003089217,0.002577982,0.002457232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001939311,"about_ca_system_score_gemma":0.003048941,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0112805,"about_ca_topic_score_gemma":0.01283352,"domain_scores_codex":[0.9961948,0.001179254,0.0002397293,0.0009265568,0.001207492,0.0002520304],"domain_scores_gemma":[0.9929604,0.002690332,0.0004087137,0.001496622,0.002239965,0.0002039985],"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":[0.0004744768,0.0001405677,0.0016384,0.0003700157,0.0002530196,0.0001420297,0.0004656378,0.66775,0.004268331,0.07304437,0.0182694,0.2331838],"study_design_scores_gemma":[0.00001164271,0.00002150211,0.0002212696,0.00001528988,0.00001028906,0.00006193531,0.00004759722,0.97694,0.001429098,0.0185057,0.00271588,0.00001973671],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.003521757,0.0003411149,0.9938881,0.0001967709,0.00005257879,0.00007607361,0.0001077847,0.0006301055,0.001185804],"genre_scores_gemma":[0.115423,0.0004807479,0.8767704,0.0003045269,0.00008832535,0.0003105315,0.0008454456,0.0003551483,0.005421779],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0112805,"threshold_uncertainty_score":0.02563512,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04531905812185061,"score_gpt":0.3426264044264536,"score_spread":0.297307346304603,"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."}}