{"id":"W2007843117","doi":"10.1016/j.aap.2015.04.014","title":"Editorial for the Journal of Accident Analysis and Prevention Special Issue of ICTIS 2013","year":2015,"lang":"en","type":"editorial","venue":"Accident Analysis & Prevention","topic":"Traffic and Road Safety","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Triage; Speed limit; Logistic regression; Poison control; Injury Severity Score; Crash; Receiver operating characteristic; Injury prevention; Medical emergency; Medicine; Occupational safety and health; Emergency medicine; Statistics; Transport engineering; Engineering; Computer science; Mathematics","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.003060774,0.0004347586,0.001492905,0.00132419,0.0001300787,0.0001116998,0.0006289334,0.0008098272,0.000400537],"category_scores_gemma":[0.0003956865,0.000345445,0.001967899,0.001679035,0.00005821596,0.0004516378,0.0001122312,0.0006112233,0.000006517495],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002509604,"about_ca_system_score_gemma":0.000196691,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002378077,"about_ca_topic_score_gemma":0.01077239,"domain_scores_codex":[0.9956781,0.0002535158,0.001744362,0.0003343656,0.001675848,0.0003137841],"domain_scores_gemma":[0.9957749,0.0006853076,0.001500524,0.0005404421,0.001361524,0.0001373592],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001984991,0.00006481412,0.002553109,0.0000258179,0.02184027,5.967136e-7,0.0003075135,0.03402392,0.000009174939,0.000002576581,0.9320009,0.008972754],"study_design_scores_gemma":[0.001797156,0.0003530832,0.00932753,0.0001145377,0.1231056,0.00000126303,0.000369252,0.00353787,0.00007626697,0.0004321591,0.8603933,0.0004919947],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.002304739,0.003110479,0.07243059,0.00003920683,0.9214252,0.0005689089,0.00001716962,0.00004104247,0.00006270586],"genre_scores_gemma":[0.03594536,0.007173772,0.0005036843,8.998476e-7,0.9545801,0.00002854256,0.0006550741,0.00005076957,0.001061751],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1012653,"threshold_uncertainty_score":0.9998997,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006828918706620624,"score_gpt":0.2676927418097451,"score_spread":0.2608638231031245,"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."}}