{"id":"W2010847373","doi":"10.1136/injuryprev-2012-040590u.36","title":"Comparing road traffic injury datasets in the Dominican Republic with Health Organisation recommendations","year":2012,"lang":"en","type":"article","venue":"Injury Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Douglas Mental Health University Institute; Douglas College","funders":"","keywords":"Identifier; Poison control; Unique identifier; Agency (philosophy); Occupational safety and health; Injury prevention; Traffic police; Human factors and ergonomics; Data quality; Environmental health; Transport engineering; Medical emergency; Medicine; Computer science; Computer security; Operations management; Engineering","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":[0.00751264,0.0003625583,0.000385068,0.005846703,0.0004968056,0.001560582,0.001217138,0.0004511096,0.003230092],"category_scores_gemma":[0.04324286,0.0002212326,0.0005361292,0.009654342,0.0003810668,0.0009418686,0.001346416,0.0004876284,0.000608251],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.002733425,"about_ca_system_score_gemma":0.004791043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.1783367,"about_ca_topic_score_gemma":0.148677,"domain_scores_codex":[0.9941294,0.001814419,0.001413795,0.0008803248,0.001280633,0.0004814638],"domain_scores_gemma":[0.9765028,0.006825421,0.006006061,0.00405888,0.005779209,0.000827653],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007431565,0.0001148403,0.8904719,0.001582505,0.0007238003,0.0001504464,0.0006186292,0.002703501,0.0004229918,0.001202158,0.06431553,0.03695054],"study_design_scores_gemma":[0.0001418433,0.00009581585,0.9439607,0.0009477789,0.0002535527,0.0001525655,0.001948217,0.002705954,0.0004968924,0.0003323001,0.04892784,0.00003647165],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.347693,0.003429521,0.002199566,0.003848318,0.0001367978,0.0006042928,0.6342255,0.0004415722,0.007421291],"genre_scores_gemma":[0.4743991,0.0011835,0.004171385,0.000438146,0.00006465508,0.0007628474,0.5176997,0.00007056342,0.001210171],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.1783367,"threshold_uncertainty_score":0.3545972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0300456111299945,"score_gpt":0.3024859550427994,"score_spread":0.2724403439128049,"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."}}