{"id":"W3081786538","doi":"10.1016/j.asoc.2020.106679","title":"A fuzzy clustering algorithm for developing predictive models in construction applications","year":2020,"lang":"en","type":"article","venue":"Applied Soft Computing","topic":"Fuzzy Logic and Control Systems","field":"Computer Science","cited_by":29,"is_retracted":false,"has_abstract":false,"ca_institutions":"Natural Sciences and Engineering Research Council of Canada; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cluster analysis; Data mining; Fuzzy clustering; Fuzzy logic; Machine learning; Artificial intelligence; Process (computing); Adaptive neuro fuzzy inference system; Fuzzy control system","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":[0.0002479667,0.0001606783,0.0002636885,0.00006810319,0.0002091009,0.0001133741,0.0005076162,0.00007946809,9.520136e-8],"category_scores_gemma":[0.0000114726,0.0001731372,0.00005075358,0.0004518974,0.00003226276,0.0001894619,0.0002767287,0.0001443772,0.00000723732],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009042078,"about_ca_system_score_gemma":0.00009376175,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001100781,"about_ca_topic_score_gemma":0.000002183397,"domain_scores_codex":[0.9985319,0.00002513175,0.0003948974,0.0005464596,0.0001647967,0.0003367797],"domain_scores_gemma":[0.9993007,0.0002013423,0.0001542965,0.000194141,0.00006911932,0.00008041527],"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":[0.000009072,0.00001241081,0.00003209427,0.00005189065,0.00002097827,0.000001323547,0.001919056,0.07980109,0.0002206325,0.2925028,0.00002342702,0.6254053],"study_design_scores_gemma":[0.0006650271,0.00002309747,0.00004033909,0.00002343682,0.00000380238,0.000006645066,0.0003263892,0.9323761,0.00004601943,0.06613015,0.0001774395,0.000181546],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0002093129,0.000065842,0.9913566,0.0004876378,0.0001206278,0.001105103,0.000003260939,0.0003560793,0.0062955],"genre_scores_gemma":[0.5350803,0.000001244707,0.4640872,0.0004631836,0.0001636149,0.000190872,0.000003674359,0.000008705193,0.000001319717],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.852575,"threshold_uncertainty_score":0.7060329,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364032910287603,"score_gpt":0.2298288110585974,"score_spread":0.2061884819557213,"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."}}