{"id":"W2094757630","doi":"10.1061/(asce)0733-9364(2001)127:6(502)","title":"Estimating Labor Production Rates for Industrial Construction Activities","year":2001,"lang":"en","type":"article","venue":"Journal of Construction Engineering and Management","topic":"Manufacturing Process and Optimization","field":"Engineering","cited_by":96,"is_retracted":false,"has_abstract":true,"ca_institutions":"PCL Construction (Canada); University of Alberta","funders":"","keywords":"Artificial neural network; Multiplier (economics); Production (economics); Estimator; Industrial production index; Production rate; Computer science; Index (typography); Industrial engineering; Econometrics; Engineering; Operations research; Statistics; Artificial intelligence; Economics; Mathematics; Microeconomics","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":[0.0001505942,0.0001092611,0.0001434361,0.0002296403,0.00006117718,0.00005975672,0.000036745,0.00004882759,0.000006276675],"category_scores_gemma":[0.00002842555,0.0001083672,0.00003381011,0.0001129011,0.00002205324,0.0003200537,0.000007849558,0.0001044777,1.65592e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004218097,"about_ca_system_score_gemma":0.000006482498,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":4.936098e-7,"about_ca_topic_score_gemma":2.038432e-7,"domain_scores_codex":[0.9994296,0.000004966258,0.0002695362,0.00008035958,0.00009966685,0.0001158825],"domain_scores_gemma":[0.999724,0.00001914927,0.0001072367,0.00005046979,0.00005866601,0.00004046177],"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":[0.00002821885,0.000005728501,0.0002397106,0.0002709361,0.0001020281,0.000002247787,0.00006231799,0.8859596,0.0002399827,0.000915324,0.0001939039,0.11198],"study_design_scores_gemma":[0.003216882,0.0002368678,0.001567845,0.0008468684,0.0003807405,0.001843705,0.001506818,0.9141918,0.01713797,0.001081261,0.05726579,0.0007234556],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4349611,0.0001919298,0.5603418,0.000120766,0.003924113,0.0002001718,0.000001955817,0.0001184185,0.0001396822],"genre_scores_gemma":[0.7405104,0.001131624,0.2570599,0.000007709084,0.001143182,0.00002435878,0.000003642788,0.00003167177,0.00008751995],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.3055493,"threshold_uncertainty_score":0.4419085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009529319624809076,"score_gpt":0.2138179442426485,"score_spread":0.2042886246178395,"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."}}