{"id":"W2087551992","doi":"10.1007/s00500-005-0478-8","title":"Hierarchical FCM in a stepwise discovery of structure in data","year":2005,"lang":"en","type":"article","venue":"Soft Computing","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":23,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"","keywords":"Cluster analysis; Tree (set theory); Hierarchical clustering; Tree structure; Computer science; Data mining; Hierarchy; Fuzzy logic; Fuzzy clustering; Data structure; Artificial intelligence; Machine learning; 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":[0.005184819,0.000496249,0.001299752,0.002597541,0.001023464,0.00167682,0.002108249,0.001292691,0.001493357],"category_scores_gemma":[0.01847218,0.0007593452,0.001530562,0.00284095,0.001012651,0.002306608,0.001880847,0.001598221,0.0004256752],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001351251,"about_ca_system_score_gemma":0.003809943,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01533588,"about_ca_topic_score_gemma":0.02498429,"domain_scores_codex":[0.9972408,0.0009217652,0.0002536944,0.0004253603,0.0009309308,0.0002274657],"domain_scores_gemma":[0.9905252,0.006676372,0.0003807276,0.001348853,0.0009310975,0.0001379074],"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":[0.0005116498,0.0003214964,0.007046717,0.0006300287,0.0004235452,0.0006546747,0.001316431,0.2408222,0.01478542,0.06035249,0.003877768,0.6692575],"study_design_scores_gemma":[0.0000166747,0.00004566543,0.0005515812,0.0000328768,0.00007604734,0.00008285194,0.00006258467,0.9656215,0.003983141,0.02818222,0.001330264,0.00001450586],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02142204,0.0003068677,0.976651,0.000183129,0.00001527697,0.0001136612,0.0001556213,0.0006498679,0.0005023991],"genre_scores_gemma":[0.1692435,0.0001465027,0.8291976,0.00009678061,0.00002249677,0.0001207458,0.0003563538,0.00004507993,0.0007708782],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01533588,"threshold_uncertainty_score":0.03049326,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01898246772828784,"score_gpt":0.2541809508311043,"score_spread":0.2351984831028164,"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."}}