{"id":"W2978991742","doi":"10.1061/9780784480823.043","title":"Level-of-Expertise Classification for Identifying Safe and Productive Masons","year":2017,"lang":"en","type":"article","venue":"","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Support vector machine; Classifier (UML); Computer science; Artificial intelligence; Machine learning; Inertial measurement unit; Outlier; Software deployment","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":[0.000768323,0.0005844978,0.0006812185,0.002006232,0.0003354698,0.0005640039,0.0006153214,0.0006914147,0.001518241],"category_scores_gemma":[0.003313641,0.0001762505,0.0004441398,0.000744401,0.0002363191,0.0007194424,0.0006987572,0.000381429,0.0008121062],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004316289,"about_ca_system_score_gemma":0.0004989806,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004502903,"about_ca_topic_score_gemma":0.004272277,"domain_scores_codex":[0.9992879,0.00009476227,0.00004681696,0.0001894724,0.0002469017,0.000134137],"domain_scores_gemma":[0.9986973,0.0004515437,0.000184192,0.0001090112,0.0004430955,0.0001148586],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0005595625,0.0005458113,0.08923893,0.0002448838,0.0001059293,0.0002949609,0.0004068148,0.04857197,0.05437187,0.0009821067,0.003595928,0.8010813],"study_design_scores_gemma":[0.0000243036,0.0004441003,0.0896734,0.00005648903,0.00005743148,0.0003390619,0.0004800461,0.8882483,0.01746842,0.001500496,0.001660537,0.00004743579],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.547127,0.0004378171,0.4474364,0.0001404729,0.00006240566,0.0002177255,0.0004255128,0.0009864254,0.003166193],"genre_scores_gemma":[0.9347785,0.0001080243,0.06353941,0.00002417181,0.00002316918,0.00006371984,0.0004322955,0.00002020775,0.001010521],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004502903,"threshold_uncertainty_score":0.008953393,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.6860713829967666,"score_gpt":0.612821462359123,"score_spread":0.07324992063764357,"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."}}