{"id":"W4220981506","doi":"10.1061/9780784483961.092","title":"Framework for Simulating Crew Motivation Impact on Productivity—A Hybrid Modeling Approach","year":2022,"lang":"en","type":"article","venue":"Construction Research Congress 2022","topic":"BIM and Construction Integration","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Crew; Productivity; Dynamism; Computer science; Fuzzy logic; Track (disk drive); Identification (biology); Industrial engineering; Industrial organization; Business; Engineering; Artificial intelligence; Economics","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":[0.0009969216,0.0007378715,0.0005657204,0.001187547,0.0005225393,0.001440789,0.001642831,0.001475837,0.003236388],"category_scores_gemma":[0.001798864,0.000445612,0.001163288,0.000828366,0.0005882852,0.0009258391,0.001281385,0.0007196067,0.0003140578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222225,"about_ca_system_score_gemma":0.001567142,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01929862,"about_ca_topic_score_gemma":0.008859653,"domain_scores_codex":[0.9996125,0.0001546545,0.00002260179,0.00006452437,0.00009192163,0.00005378442],"domain_scores_gemma":[0.9994034,0.0003446701,0.00007322941,0.00004129003,0.00009810913,0.00003935322],"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":[0.00001909828,0.00005159479,0.0009192065,0.00002588109,0.000025634,0.00003945624,0.00007623724,0.9801174,0.0009088627,0.0131531,0.0001118739,0.00455162],"study_design_scores_gemma":[0.000005130937,0.00001125084,0.000111087,0.000004034076,0.000005492395,0.000004786374,0.00001969528,0.9972319,0.0001042448,0.002117892,0.000380008,0.000004534199],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.06556737,0.0001673772,0.9172303,0.0003091003,0.00003644705,0.0001281589,0.0003032443,0.0003501653,0.01590783],"genre_scores_gemma":[0.8304902,0.0003301007,0.1636852,0.00006624642,0.00002574319,0.0005654554,0.000240666,0.00006538683,0.004531024],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01929862,"threshold_uncertainty_score":0.03837258,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0757413966445981,"score_gpt":0.3470051589744345,"score_spread":0.2712637623298363,"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."}}