{"id":"W4410106010","doi":"10.1016/j.aei.2025.103367","title":"Integrated fuzzy system dynamics–fuzzy agent-based modeling of construction crew motivation and productivity","year":2025,"lang":"en","type":"article","venue":"Advanced Engineering Informatics","topic":"BIM and Construction Integration","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada First Research Excellence Fund; University of Alberta","keywords":"Crew; Productivity; Fuzzy logic; Computer science; Engineering; Artificial intelligence; Aeronautics; Economics","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":[0.00009867367,0.0001818474,0.0002190745,0.0003016358,0.00004745716,0.00002917638,0.00006446952,0.0001019619,9.083641e-7],"category_scores_gemma":[0.00005691967,0.0001912163,0.00003725373,0.0004302959,0.00003269198,0.0004640719,0.0000126076,0.0001897965,0.000001013603],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002428019,"about_ca_system_score_gemma":0.00003270656,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006884736,"about_ca_topic_score_gemma":0.000004364718,"domain_scores_codex":[0.9991199,0.000006867277,0.0005229111,0.00008569824,0.0001123755,0.000152187],"domain_scores_gemma":[0.9995179,0.00003425918,0.00007483991,0.0001824704,0.0001552823,0.00003528206],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000007133416,0.000003835514,0.0002065239,0.001096142,0.00003148699,9.702666e-8,0.00009180463,0.9274018,0.001012145,0.03201986,0.000003593574,0.03812553],"study_design_scores_gemma":[0.0003123968,0.00001290608,0.0001413772,0.0004167634,0.00002421644,0.000007290155,0.0008306899,0.9940238,0.003822431,0.0001558479,0.0001034177,0.0001488715],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2847632,0.00007702616,0.7119626,0.000008328685,0.0006075337,0.0001696391,0.0000145555,0.0004076395,0.001989456],"genre_scores_gemma":[0.9405054,0.00001923366,0.05935953,0.000004221815,0.00001419478,0.00002616865,0.0000471684,0.00001524187,0.000008823032],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.6557422,"threshold_uncertainty_score":0.7797576,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004842735871657765,"score_gpt":0.1813779162352967,"score_spread":0.1765351803636389,"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."}}