{"id":"W4392914604","doi":"10.1061/9780784485293.076","title":"Evaluating Machine Learning and AHP Tools for the Pre-Qualification of Construction Contractors Based on Occupational Health and Safety Criteria","year":2024,"lang":"en","type":"article","venue":"","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Analytic hierarchy process; Hazardous waste; Process (computing); Occupational safety and health; Hazard; Construction industry; Risk analysis (engineering); Computer science; Construction engineering; Transport engineering; Business; Engineering; Operations research; Waste management","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.01839584,0.00178945,0.00155721,0.005764771,0.00100082,0.002368972,0.001277588,0.001239306,0.001668244],"category_scores_gemma":[0.04099518,0.0004832153,0.001255829,0.003462337,0.0008402094,0.001434924,0.00190851,0.001729489,0.0002130445],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003501784,"about_ca_system_score_gemma":0.005682956,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01780317,"about_ca_topic_score_gemma":0.01454061,"domain_scores_codex":[0.9867765,0.008333393,0.001126695,0.0007049379,0.002462724,0.0005956434],"domain_scores_gemma":[0.9474218,0.04164072,0.002918062,0.0008264902,0.006373913,0.0008189322],"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":[0.0008545265,0.001083648,0.01965991,0.001197914,0.0003965014,0.00016116,0.001089468,0.7508029,0.001831932,0.007031701,0.00172315,0.2141671],"study_design_scores_gemma":[0.00005575239,0.0003024614,0.002495898,0.00009434861,0.00003394464,0.00001422788,0.0006573765,0.9919055,0.001020498,0.002929276,0.0004637066,0.00002714559],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4098022,0.0009199751,0.5775028,0.001138535,0.0001471698,0.002143725,0.0008241324,0.0008106501,0.006710842],"genre_scores_gemma":[0.7091889,0.0002238799,0.288691,0.00009077205,0.00002794338,0.0007593867,0.0005636549,0.00002564801,0.0004289048],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01839584,"threshold_uncertainty_score":0.09728765,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.239444963422261,"score_gpt":0.5870476691304606,"score_spread":0.3476027057081995,"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."}}