{"id":"W4388439362","doi":"10.7202/1106605ar","title":"Lateral damage and point of impactin intersection crashes: Implications for injury","year":2023,"lang":"en","type":"article","venue":"Assurances et gestion des risques","topic":"Traffic and Road Safety","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Spinal Cord Injury BC; University of Toronto","funders":"Social Sciences and Humanities Research Council of Canada; Natural Sciences and Engineering Research Council of Canada","keywords":"Fender; Crash; Front (military); Intersection (aeronautics); Vehicle type; Forensic engineering; Aeronautics; Engineering; Structural engineering; Transport engineering; Computer science","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.001593509,0.0008204084,0.0008418419,0.002763745,0.0006978422,0.001837228,0.001260536,0.001511533,0.007582869],"category_scores_gemma":[0.01244838,0.0003585058,0.001685095,0.002213966,0.001387579,0.002138046,0.002003473,0.00114069,0.000499822],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000727533,"about_ca_system_score_gemma":0.0008971594,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01583628,"about_ca_topic_score_gemma":0.01264047,"domain_scores_codex":[0.9974697,0.0008585438,0.0001931017,0.0004407222,0.0006410482,0.000396962],"domain_scores_gemma":[0.9921284,0.00286095,0.003110111,0.0003093008,0.0008462282,0.0007449553],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002228751,0.00006054303,0.9867883,0.00007353656,0.0001353757,0.0004801073,0.0002326336,0.0003015614,0.0001932575,0.0001856823,0.0002264034,0.01109976],"study_design_scores_gemma":[0.000004289249,0.0001316545,0.9962715,0.00008053368,0.00007717613,0.001178939,0.0006925839,0.0007449188,0.00006760075,0.0004411571,0.0002959293,0.00001367205],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.983,0.009670426,0.0009210845,0.002021587,0.00004847698,0.00002685235,0.0002955773,0.00001587358,0.004000026],"genre_scores_gemma":[0.9965013,0.002348315,0.0001988375,0.0001150335,0.0001009614,0.00001113001,0.0001315688,0.000005586729,0.0005872918],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01583628,"threshold_uncertainty_score":0.03148818,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02575373461750076,"score_gpt":0.2892980360757478,"score_spread":0.263544301458247,"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."}}