{"id":"W4403511942","doi":"10.1109/iv64223.2024.00032","title":"Visual Analytics of Motor Vehicle Accidents","year":2024,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Visual analytics; Computer science; Analytics; Visualization; Automotive engineering; Human–computer interaction; Data science; Artificial intelligence; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.00005127436,0.00005970459,0.00008717817,0.0000819211,0.00001147653,0.000007479363,0.00008681454,0.00008791818,0.000212288],"category_scores_gemma":[0.00000501947,0.00005472239,0.00004055223,0.0001559867,0.00002516854,0.00006400133,0.00002371768,0.0001096905,0.0001579007],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002356302,"about_ca_system_score_gemma":0.000009246985,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005556646,"about_ca_topic_score_gemma":0.000005195848,"domain_scores_codex":[0.9996338,0.000002757035,0.0001306816,0.00007290113,0.00005329759,0.0001065812],"domain_scores_gemma":[0.9998453,0.0000232019,0.000004794394,0.00009734177,0.000008776012,0.00002056636],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00004612392,0.0002194999,0.04231096,0.001167293,0.00152373,0.0002292904,0.0008717421,0.0237984,0.3460865,0.1391578,0.01708353,0.427505],"study_design_scores_gemma":[0.0001090772,0.00005131453,0.01546023,0.00002653793,0.00002688772,0.000005259107,0.0000529278,0.8992226,0.07918683,0.001245104,0.004471266,0.0001419289],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9774164,0.0004988935,0.009826074,0.00007655672,0.0002084092,0.000051143,0.00000396141,0.001277864,0.01064072],"genre_scores_gemma":[0.9987686,0.00003981073,0.0003080278,0.0000115098,0.00002089516,0.000002172001,0.000001313724,0.00001384001,0.0008338368],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8754242,"threshold_uncertainty_score":0.2324405,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.006492005113103333,"score_gpt":0.235165490162861,"score_spread":0.2286734850497576,"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."}}