{"id":"W2031530749","doi":"10.1080/15389588.2012.732718","title":"Frontal Impact Response for Pole Crash Scenarios","year":2012,"lang":"en","type":"article","venue":"Traffic Injury Prevention","topic":"Automotive and Human Injury Biomechanics","field":"Medicine","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Transport Canada","keywords":"Crash; Poison control; Injury prevention; Forensic engineering; Engineering; Occupational safety and health; Human factors and ergonomics; Structural engineering; Physical medicine and rehabilitation; Aeronautics; Computer science; Medical emergency; Medicine","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0002954302,0.0004743221,0.0002153998,0.0005758264,0.0002624702,0.0003422975,0.000333058,0.000356175,0.003287489],"category_scores_gemma":[0.001452367,0.000143127,0.0002375406,0.0002142131,0.0001844081,0.0003369819,0.0005675975,0.0001867242,0.0003699816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000472617,"about_ca_system_score_gemma":0.0002506065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004692291,"about_ca_topic_score_gemma":0.008223088,"domain_scores_codex":[0.9997464,0.00003167733,0.00001561438,0.00003966572,0.0001164449,0.00005018542],"domain_scores_gemma":[0.99965,0.00007802093,0.00008561178,0.00002680192,0.0001330404,0.00002663531],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.004179283,0.0006136731,0.5260255,0.0004433156,0.0001734739,0.00328077,0.001115418,0.212154,0.1761831,0.0005442318,0.001546907,0.07374029],"study_design_scores_gemma":[0.00006571145,0.006774442,0.6718898,0.00008367162,0.0001102378,0.002455388,0.002706746,0.2431351,0.07033421,0.0005362522,0.001838294,0.00007015504],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969569,0.00002969393,0.002078505,0.0000122779,0.000002865503,0.00003236462,0.0001303405,0.00004026621,0.0007168101],"genre_scores_gemma":[0.9990097,0.00002920093,0.0005125094,0.000004747748,8.121084e-7,0.000009643497,0.0001724209,0.000003378146,0.0002575857],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004692291,"threshold_uncertainty_score":0.01099777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02750505909629132,"score_gpt":0.3482037649956705,"score_spread":0.3206987058993792,"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."}}