{"id":"W2153602116","doi":"10.1061/9780784412329.114","title":"Assessing Productivity Improvement of Quick Connection Systems in the Steel Construction Industry Using Building Information Modeling (BIM)","year":2012,"lang":"en","type":"article","venue":"Construction Research Congress 2012","topic":"BIM and Construction Integration","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Productivity; Building information modeling; Schedule; Work (physics); Engineering; Construction industry; Computer science; Construction engineering; Manufacturing engineering; Mechanical engineering; Scheduling (production processes); Operations management","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":[0.003151265,0.0002342939,0.0002900167,0.0008824457,0.0003691438,0.0003724234,0.000208612,0.0004110581,0.00004416806],"category_scores_gemma":[0.0002234259,0.0002085327,0.00006655866,0.00108839,0.000414469,0.006547226,0.00005249872,0.001355522,0.000006823843],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004869759,"about_ca_system_score_gemma":0.0001558776,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003996234,"about_ca_topic_score_gemma":0.00002083075,"domain_scores_codex":[0.9970362,0.0004122477,0.0008360277,0.0002145273,0.0008640448,0.0006369409],"domain_scores_gemma":[0.9983487,0.0001542096,0.0002324862,0.000381887,0.0007677956,0.0001149314],"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":[0.0001281922,0.0001823932,0.05845993,0.001425062,0.0002288808,0.000001761186,0.002318905,0.279512,0.1534023,0.1156833,0.0003053745,0.388352],"study_design_scores_gemma":[0.001662649,0.0001044307,0.004770717,0.0007826619,0.0000875959,0.0008728601,0.07630698,0.8700119,0.04018914,0.001547523,0.002855143,0.0008083405],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9452938,0.0006728798,0.04693178,0.00005422255,0.005113052,0.0008310268,0.00001396289,0.0001149916,0.0009743135],"genre_scores_gemma":[0.997335,0.0000396823,0.001946655,0.000005614775,0.000513889,0.0001167769,0.00001508763,0.00002153351,0.000005819423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5905,"threshold_uncertainty_score":0.8503717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08006876967882427,"score_gpt":0.3436258980644309,"score_spread":0.2635571283856067,"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."}}