{"id":"W2752386075","doi":"10.13031/jash.11959","title":"Hazard Identification and Risk Assessment for Improving Farm Safety on Canadian Farms","year":2017,"lang":"en","type":"article","venue":"Journal of Agricultural Safety and Health","topic":"Agriculture and Farm Safety","field":"Agricultural and Biological Sciences","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"Natural Sciences and Engineering Research Council of Canada; Vital Strategies","keywords":"Occupational safety and health; Hazard; Risk assessment; Risk analysis (engineering); Poison control; Hazard analysis; Protocol (science); Work (physics); Environmental health; Agriculture; Injury prevention; Personal protective equipment; Intervention (counseling); Business; Engineering; Computer security; Computer science; Medicine; Reliability engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.007548527,0.000955092,0.0004919225,0.004257869,0.003507358,0.001422238,0.002136539,0.0008167622,0.00557973],"category_scores_gemma":[0.01710703,0.0004254275,0.001186878,0.002141787,0.0006966415,0.001118752,0.002558671,0.0008120899,0.0007433412],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01419049,"about_ca_system_score_gemma":0.04398504,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.480536,"about_ca_topic_score_gemma":0.7019109,"domain_scores_codex":[0.9954777,0.001096953,0.0004826376,0.0002935206,0.002230128,0.0004190126],"domain_scores_gemma":[0.9896775,0.001440566,0.001326194,0.0004398597,0.006701696,0.0004141351],"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":[0.0008770407,0.001741042,0.3098003,0.003505772,0.0001658316,0.0009703133,0.009599229,0.01802647,0.01554042,0.005296592,0.01199369,0.6224833],"study_design_scores_gemma":[0.000291174,0.003825402,0.8018261,0.002837721,0.0005860119,0.0007510233,0.02748295,0.04354078,0.02135097,0.007759267,0.08926515,0.0004834712],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7819289,0.0019781,0.1043802,0.004044737,0.0002008225,0.02615525,0.00705474,0.0009488894,0.07330856],"genre_scores_gemma":[0.7035161,0.003529903,0.2667939,0.000505047,0.00003796158,0.005499478,0.003699711,0.00005523287,0.01636264],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.519464,"threshold_uncertainty_score":0.955478,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02364580330396775,"score_gpt":0.282451423780284,"score_spread":0.2588056204763162,"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."}}