{"id":"W4404965137","doi":"10.1080/24725838.2024.2432450","title":"Analyzing Occupational Accidents and Exoskeleton Potential in the Construction Industry in Québec, Canada","year":2024,"lang":"en","type":"article","venue":"IISE Transactions on Occupational Ergonomics and Human Factors","topic":"Occupational Health and Safety Research","field":"Health Professions","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Mitacs","keywords":"Exoskeleton; Human factors and ergonomics; Intervention (counseling); Occupational safety and health; Injury prevention; Productivity; Poison control; Suicide prevention; Engineering; Forensic engineering; Applied psychology; Medicine; Psychology; Physical medicine and rehabilitation; Environmental health; Nursing; Economic growth; Pathology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004777325,0.0001835705,0.0001942209,0.0004879856,0.0009292354,0.00005752489,0.0001174643,0.0003049175,0.0004107264],"category_scores_gemma":[0.00003145898,0.0001535548,0.0000424055,0.0003128268,0.00009746653,0.0002510805,0.000009448629,0.001778636,0.000006884545],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000752716,"about_ca_system_score_gemma":0.002914329,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.5094509,"about_ca_topic_score_gemma":0.8661097,"domain_scores_codex":[0.9981219,0.0002533864,0.0005914858,0.0003595656,0.0003208535,0.0003528003],"domain_scores_gemma":[0.9985911,0.0009836861,0.00007698627,0.0001354445,0.00006801633,0.000144719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005463265,0.00008882205,0.9792451,0.0001650345,0.0000370923,0.00001302788,0.0009807578,0.001991522,0.0000165406,0.007679974,0.0003958982,0.008839942],"study_design_scores_gemma":[0.0004711837,0.00004449826,0.9947116,0.0001112197,0.00001155047,0.000003378327,0.001039202,0.001360595,0.000003150099,0.000278624,0.001823197,0.0001418142],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9966155,0.0001339344,0.0005596764,0.001231382,0.0004554354,0.0005415865,0.0002453097,0.00001995632,0.0001972642],"genre_scores_gemma":[0.9990761,0.0001075997,0.00005781424,0.0002631641,0.000115905,0.0001205135,0.0001369095,0.0000159476,0.000106055],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3566588,"threshold_uncertainty_score":0.7727387,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04806530145358584,"score_gpt":0.3888785574973057,"score_spread":0.3408132560437199,"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."}}