{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001252666,0.000228164,0.0002416379,0.0006442881,0.00123256,0.0001683697,0.0002532973,0.0000813268,0.0005606218],"category_scores_gemma":[0.0006791865,0.000236329,0.0001499403,0.0008584802,0.0001539867,0.000324812,0.0000987173,0.001364812,0.000007171298],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000662126,"about_ca_system_score_gemma":0.000142416,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002103129,"about_ca_topic_score_gemma":8.397848e-7,"domain_scores_codex":[0.9973722,0.0003059892,0.0003698671,0.0005121023,0.0009113731,0.0005284565],"domain_scores_gemma":[0.9984263,0.0005087705,0.00007213978,0.0004214539,0.0004550459,0.0001163598],"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":[0.0001487755,0.00004573276,0.00061482,0.00006601167,0.00007838153,0.000001366049,0.0001263326,0.8717488,0.0009967738,0.0394813,0.0008722067,0.08581951],"study_design_scores_gemma":[0.0004040446,0.0001738876,0.00007129978,0.00002717248,0.00001014101,0.000069091,0.001478947,0.9726048,0.001714635,0.02164448,0.001552633,0.0002489331],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6622096,0.0002617133,0.3303871,0.0001456125,0.002658531,0.001352312,0.0001797709,0.000473894,0.002331429],"genre_scores_gemma":[0.9916352,0.00001608287,0.006466036,0.00001321457,0.0004641462,0.001070855,0.0001360614,0.00006368285,0.0001346968],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3294256,"threshold_uncertainty_score":0.9637219,"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."}}