{"id":"W2964040819","doi":"10.1609/aaai.v32i1.12221","title":"Clustering - What Both Theoreticians and Practitioners Are Doing Wrong","year":2018,"lang":"en","type":"article","venue":"","topic":"Advanced Clustering Algorithms Research","field":"Computer Science","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cluster analysis; Computer science; Conceptual clustering; Machine learning; Selection (genetic algorithm); Correlation clustering; Artificial intelligence; Task (project management); Implementation; Consensus clustering; Constrained clustering; CURE data clustering algorithm; Data mining; Engineering; Software engineering","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":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.03636779,0.001425346,0.002496088,0.005398404,0.007151028,0.01452687,0.006290438,0.01440047,0.005349004],"category_scores_gemma":[0.1026139,0.001078902,0.001673335,0.008456095,0.02733896,0.03144962,0.005365825,0.0114165,0.00516445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004902287,"about_ca_system_score_gemma":0.00468672,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00667167,"about_ca_topic_score_gemma":0.005280768,"domain_scores_codex":[0.9676356,0.01600517,0.001429569,0.004115466,0.009821975,0.0009922732],"domain_scores_gemma":[0.8901276,0.07343911,0.002915053,0.01722171,0.01361426,0.00268221],"domain_codex":null,"domain_gemma":"methods","domain_candidate":"methods","domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.00005330583,0.00003360712,0.001347405,0.001109637,0.000143315,0.00009635764,0.002051652,0.0027252,0.0002442926,0.6493816,0.1929362,0.1498774],"study_design_scores_gemma":[0.00001445104,0.00001216816,0.0003250829,0.0007683446,0.00001603476,0.0001466228,0.001598592,0.002098217,0.0002832613,0.8962738,0.09840059,0.00006284945],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.002502769,0.06476758,0.1684558,0.7300433,0.01193344,0.00005474622,0.0003135352,0.0008875402,0.02104126],"genre_scores_gemma":[0.1842929,0.1533993,0.3653677,0.2392231,0.03363594,0.0004687136,0.001180266,0.002022569,0.02040952],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.9636322,"threshold_uncertainty_score":0.1923336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0169064493828706,"score_gpt":0.3005511694067407,"score_spread":0.2836447200238701,"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."}}