{"id":"W1996395472","doi":"10.1016/j.jhydrol.2011.02.027","title":"A Fuzzy C-Means approach for regionalization using a bivariate homogeneity and discordancy approach","year":2011,"lang":"en","type":"article","venue":"Journal of Hydrology","topic":"Hydrology and Drought Analysis","field":"Environmental Science","cited_by":80,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Bivariate analysis; Univariate; Statistics; Homogeneity (statistics); Copula (linguistics); Econometrics; Multivariate statistics; Bivariate data; Fuzzy logic; Mathematics; Multivariate analysis; Hierarchical clustering; Cluster analysis; Computer science","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006093908,0.0001190687,0.0002957511,0.0001000713,0.0001448311,0.000007147513,0.000179131,0.0001267499,0.00007831263],"category_scores_gemma":[0.0000422745,0.00009379632,0.0001249199,0.0001816548,0.0002447055,0.0002298814,0.0000737462,0.0001376237,0.000002670421],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003724319,"about_ca_system_score_gemma":0.00001618352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008905997,"about_ca_topic_score_gemma":0.0000208308,"domain_scores_codex":[0.998951,0.0001359762,0.0003536206,0.0002115168,0.0001238387,0.0002240231],"domain_scores_gemma":[0.9993625,0.00003272307,0.0003581634,0.0001348842,0.00001824117,0.00009350593],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.002121899,0.00224924,0.8321605,0.00009759367,0.001053572,0.00009667308,0.008977547,0.1254288,0.01477987,0.009096582,0.001263811,0.002673986],"study_design_scores_gemma":[0.004015061,0.001614299,0.06553669,0.00001408362,0.001524413,0.004267921,0.0003594379,0.8195642,0.0007284704,0.1000791,0.001569288,0.000727044],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6610664,0.0001310025,0.3339537,0.00006601882,0.00005171293,0.0001001776,0.000001954654,0.00000508627,0.004623948],"genre_scores_gemma":[0.9159698,0.00003255528,0.08365625,0.000187495,0.00007750166,0.000005021019,0.000004331361,0.00001019359,0.00005684759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7666238,"threshold_uncertainty_score":0.3824903,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03948111702484558,"score_gpt":0.2477566509279384,"score_spread":0.2082755339030928,"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."}}