{"id":"W2148103603","doi":"10.1136/ip.2003.004143","title":"Injury outcome indicators: the development of a validation tool: Table 1","year":2005,"lang":"en","type":"article","venue":"Injury Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"Health Canada","funders":"Health Research Council of New Zealand","keywords":"Consistency (knowledge bases); Population; Poison control; Injury prevention; Human factors and ergonomics; Occupational safety and health; Forensic engineering; Transport engineering; Psychology; Engineering; Computer science; Medicine; Medical emergency; Environmental health; Pathology","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0003804137,0.00009346298,0.0001067948,0.00008828752,0.00007133945,0.00001207181,0.0001255617,0.00006804233,0.0001216908],"category_scores_gemma":[0.00001077288,0.00007259723,0.00004952135,0.0002158335,0.00001700747,0.0001828019,0.00002723481,0.0001034627,0.000075566],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00007066446,"about_ca_system_score_gemma":0.00003362805,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":8.989978e-7,"about_ca_topic_score_gemma":0.000005276116,"domain_scores_codex":[0.9991555,0.00002735801,0.0004293684,0.00009303409,0.0001612052,0.0001335897],"domain_scores_gemma":[0.9997063,0.00001399597,0.00007191791,0.0001683533,0.00001746986,0.00002192268],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003473038,0.0001322288,0.007685361,0.0001086072,0.000106031,1.265785e-7,0.001515962,0.006306905,0.006639051,0.0009719998,0.002902645,0.9735963],"study_design_scores_gemma":[0.0009015905,0.0001358181,0.2988328,0.0001990327,0.0001252594,0.000003415342,0.0002915121,0.004641104,0.2842496,0.0005963205,0.4092509,0.0007727042],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9792598,0.00006983933,0.018275,0.00005041202,0.0002296581,0.0002119243,0.000008508712,0.0001752947,0.001719591],"genre_scores_gemma":[0.9940253,0.00001192838,0.005249661,0.00001177695,0.00008306453,0.00003024816,0.00002288408,0.00001535748,0.0005497454],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9728236,"threshold_uncertainty_score":0.2960429,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01422286211773933,"score_gpt":0.2667558692096204,"score_spread":0.252533007091881,"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."}}