{"id":"W4367171980","doi":"10.18280/mmep.100242","title":"Assessment of Construction Risk Management Maturity Using Hybrid Fuzzy Analytical Hierarchy Process and Fuzzy Synthetic Approach: Iraq as Case Study","year":2023,"lang":"en","type":"article","venue":"Mathematical Modelling and Engineering Problems","topic":"Construction Project Management and Performance","field":"Decision Sciences","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Fuzzy logic; Maturity (psychological); Hierarchy; Process (computing); Computer science; Risk analysis (engineering); Engineering; Artificial intelligence; Business; Psychology; Economics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004388387,0.0004934933,0.0003825602,0.002695919,0.001071836,0.001529372,0.0008093772,0.001175643,0.0007258423],"category_scores_gemma":[0.00376579,0.0002387715,0.0008287312,0.002035146,0.0007912702,0.001018267,0.0009315126,0.0005690706,0.00009698232],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003057192,"about_ca_system_score_gemma":0.001885147,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0112128,"about_ca_topic_score_gemma":0.0147678,"domain_scores_codex":[0.9979928,0.001272893,0.00009064167,0.000105951,0.0003727624,0.0001650409],"domain_scores_gemma":[0.9966408,0.001948524,0.000372762,0.0001582109,0.0007601986,0.0001194863],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.001050331,0.003991762,0.166631,0.001799321,0.0004061167,0.01625352,0.03864219,0.3895309,0.02085102,0.06045924,0.006129832,0.2942547],"study_design_scores_gemma":[0.0001986069,0.002197497,0.07503081,0.0005951463,0.0002959816,0.001864072,0.05917889,0.8103673,0.01712714,0.01322056,0.01966065,0.0002632467],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9632372,0.0003251165,0.02796947,0.0005014454,0.000009875754,0.0003629022,0.0001133854,0.00003806757,0.007442581],"genre_scores_gemma":[0.9664601,0.000282057,0.03211985,0.00003176365,0.00000491361,0.0001403276,0.00005673447,0.000005021304,0.0008991724],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0112128,"threshold_uncertainty_score":0.02320832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08220559521348211,"score_gpt":0.3414861246455032,"score_spread":0.2592805294320211,"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."}}