{"id":"W3135173030","doi":"10.1049/itr2.12053","title":"Evaluation of emergency driving behaviour and vehicle collision risk in connected vehicle environment: A deep learning approach","year":2021,"lang":"en","type":"article","venue":"IET Intelligent Transport Systems","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Collision; Motor vehicle crash; Automotive engineering; Vehicle safety; Aeronautics; Computer science; Transport engineering; Engineering; Artificial intelligence; Computer security; Poison control; Human factors and ergonomics; Medical emergency; Medicine","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":[],"consensus_categories":[],"category_scores_codex":[0.001284194,0.0001867088,0.0003366935,0.0001189924,0.00008074255,0.000006539495,0.000106094,0.0002498733,0.00007966041],"category_scores_gemma":[0.00004098306,0.000209518,0.00007076332,0.0002711186,0.00003747176,0.00009827005,0.00001571702,0.0003910777,0.000008823336],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000140839,"about_ca_system_score_gemma":0.00002499837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001053774,"about_ca_topic_score_gemma":0.0001458844,"domain_scores_codex":[0.9981336,0.0002136317,0.0006830856,0.000315497,0.000401662,0.0002524993],"domain_scores_gemma":[0.9994483,0.00004625532,0.0001096761,0.000246551,0.00009053494,0.00005869799],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000008826149,0.0001208493,0.4053583,0.0001118801,0.00007398612,0.00001040378,0.001750396,0.5808758,0.004975961,0.0001427317,0.000001646204,0.006569137],"study_design_scores_gemma":[0.0005244471,0.00004631349,0.1660626,0.00008537045,0.0001750046,0.000008895186,0.001820226,0.8204004,0.01044811,0.00005278626,0.0001503495,0.0002255142],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9661463,0.004483693,0.02807952,0.000007062149,0.0002107645,0.0004226915,0.00001126632,0.0001630413,0.0004756743],"genre_scores_gemma":[0.9967007,0.002941161,0.0001363368,7.391616e-7,0.0000171722,0.00007734146,0.00005207619,0.00003452198,0.00003994028],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2395246,"threshold_uncertainty_score":0.8543897,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01773811941754338,"score_gpt":0.2256603109188693,"score_spread":0.207922191501326,"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."}}