{"id":"W4232589861","doi":"10.1037/e511082013-001","title":"Development of National Surveillance Program for Agriculture Injury: A Canadian Example","year":2011,"lang":"en","type":"dataset","venue":"PsycEXTRA Dataset","topic":"Agriculture and Farm Safety","field":"Agricultural and Biological Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Agriculture; Injury surveillance; Business; Environmental planning; Environmental science; Geography; Environmental health; Injury prevention; Poison control; Archaeology; Medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001340454,0.001381817,0.0009959438,0.005074242,0.001286737,0.001602878,0.002569576,0.0014359,0.0125738],"category_scores_gemma":[0.007650894,0.0005833204,0.001624984,0.01386427,0.0003548449,0.0006270778,0.0008913483,0.001412821,0.005334543],"about_ca_system_candidate":true,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.01584645,"about_ca_system_score_gemma":0.02833493,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9723248,"about_ca_topic_score_gemma":0.9837393,"domain_scores_codex":[0.9987071,0.0001131644,0.0001194746,0.0002695534,0.0005020212,0.0002886758],"domain_scores_gemma":[0.9936448,0.0006645527,0.0004136192,0.0005965395,0.004211545,0.000468859],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0001656286,0.00004494349,0.01507649,0.0005823055,0.0001506485,0.00006360925,0.00006155027,0.002161097,0.0001005412,0.001001319,0.9731294,0.007462411],"study_design_scores_gemma":[0.0004876923,0.00003942733,0.2243601,0.0007949561,0.0003048,0.0001237576,0.0004700423,0.00583405,0.0007839891,0.0009528717,0.7657234,0.0001248263],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.001077037,0.0001250725,0.0000815743,0.0001611302,0.0000124457,0.00002822336,0.9974174,0.00006608658,0.001031037],"genre_scores_gemma":[0.003879324,0.0002030491,0.0004991466,0.00006169475,0.000005639903,0.00007514731,0.9934773,0.0000244875,0.001774068],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.9841536,"threshold_uncertainty_score":0.1149746,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04846007301016975,"score_gpt":0.2756313437454109,"score_spread":0.2271712707352411,"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."}}