{"id":"W2951747536","doi":"10.1145/3321386","title":"Hierarchical Clustering","year":2019,"lang":"en","type":"article","venue":"Journal of the ACM","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":207,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"Engineering and Physical Sciences Research Council; Alan Turing Institute; National Science Foundation","keywords":"Cluster analysis; Hierarchical clustering; Granularity; Constrained clustering; Computer science; Correlation clustering; Data mining; Similarity (geometry); Hierarchy; Fuzzy clustering; Set (abstract data type); Function (biology); Canopy clustering algorithm; Mathematics; Artificial intelligence","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":[0.003429312,0.002612446,0.002875324,0.006708002,0.002982405,0.006115853,0.006056515,0.00269493,0.0275878],"category_scores_gemma":[0.01273325,0.001073756,0.003972859,0.008202929,0.001456734,0.005095282,0.005589416,0.002389646,0.02362363],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003343682,"about_ca_system_score_gemma":0.004433169,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009738219,"about_ca_topic_score_gemma":0.01697514,"domain_scores_codex":[0.9924628,0.001624363,0.0004931904,0.002461773,0.002420144,0.0005377101],"domain_scores_gemma":[0.9938301,0.001216544,0.0003931941,0.002348131,0.001975198,0.0002367984],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0002992357,0.0001673954,0.004265345,0.0017766,0.0008212059,0.0002866961,0.0007755331,0.07483504,0.004662727,0.1340771,0.2317518,0.5462813],"study_design_scores_gemma":[0.00008430688,0.0001190639,0.002808784,0.0005067384,0.0002821847,0.000586517,0.0007320257,0.3119563,0.00611871,0.2863572,0.3902747,0.0001735428],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.002632773,0.002177528,0.9594924,0.0007473163,0.0002957739,0.000735456,0.008067493,0.006840693,0.01901047],"genre_scores_gemma":[0.06916197,0.002484805,0.8647962,0.001100556,0.0003414628,0.001035596,0.03783154,0.00233954,0.02090835],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0275878,"threshold_uncertainty_score":0.0922904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02099676116478523,"score_gpt":0.2989714861892535,"score_spread":0.2779747250244682,"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."}}