{"id":"W2097507414","doi":"10.1109/icdm.2006.151","title":"Speedup Clustering with Hierarchical Ranking","year":2006,"lang":"en","type":"article","venue":"Proceedings","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada's Michael Smith Genome Sciences Centre","keywords":"Speedup; Cluster analysis; Computer science; Ranking (information retrieval); Pairwise comparison; Data mining; Hierarchical clustering; Algorithm; Artificial intelligence; Parallel computing","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":[0.001419744,0.001186124,0.001152997,0.001215853,0.000817773,0.001106244,0.001411866,0.001012487,0.006382778],"category_scores_gemma":[0.006596499,0.0005145454,0.000828332,0.002218371,0.000581513,0.002713999,0.001747585,0.0009553032,0.004030303],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0010497,"about_ca_system_score_gemma":0.001507595,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0081898,"about_ca_topic_score_gemma":0.01264875,"domain_scores_codex":[0.9982052,0.0004021,0.00008085638,0.0003001482,0.0008679875,0.0001437794],"domain_scores_gemma":[0.9967456,0.00100467,0.0001689336,0.001401685,0.0005843518,0.00009468349],"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":[0.0003853699,0.0001652041,0.00196713,0.0003369715,0.0001223234,0.0001147672,0.0003144566,0.2145191,0.04103241,0.03106062,0.01874742,0.6912342],"study_design_scores_gemma":[0.0001161864,0.0001560638,0.001318108,0.00001693641,0.00004831331,0.0002064924,0.0001590507,0.9224809,0.02311057,0.03728469,0.01505921,0.00004344528],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02901837,0.0004088618,0.9580048,0.000390201,0.0001427193,0.0001532074,0.0002229653,0.006338497,0.005320408],"genre_scores_gemma":[0.2146717,0.0002075546,0.778137,0.0001490389,0.00008394255,0.0001282632,0.0007867753,0.0005466737,0.005289061],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0081898,"threshold_uncertainty_score":0.02135259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009744494059777837,"score_gpt":0.2418840382192615,"score_spread":0.2321395441594837,"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."}}