{"id":"W2946562067","doi":"10.1049/iet-its.2018.5409","title":"Vision‐based traffic accident detection using sparse spatio‐temporal features and weighted extreme learning machine","year":2019,"lang":"en","type":"article","venue":"IET Intelligent Transport Systems","topic":"Video Surveillance and Tracking Methods","field":"Computer Science","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University","funders":"","keywords":"Computer science; Artificial intelligence; Extreme learning machine; Traffic accident; Computer vision; Pattern recognition (psychology); Machine learning; Engineering; Artificial neural network; Transport engineering","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006018265,0.000496398,0.0008079715,0.001757579,0.0002493437,0.0005633982,0.0009424373,0.0005939487,0.0004591201],"category_scores_gemma":[0.002004751,0.0002601991,0.0008276773,0.0009207723,0.000328892,0.000911197,0.0007860048,0.0007230341,0.0002019231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003761402,"about_ca_system_score_gemma":0.0004387989,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002384416,"about_ca_topic_score_gemma":0.002100621,"domain_scores_codex":[0.9994507,0.00009526007,0.00003504115,0.0001572575,0.0001854255,0.00007634576],"domain_scores_gemma":[0.9993742,0.0001615409,0.0001264746,0.00007600125,0.0002129052,0.00004884636],"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":[0.0005011542,0.0004442566,0.01101646,0.0001254165,0.000180769,0.0002765066,0.0001525839,0.2805561,0.02974844,0.003330265,0.004077072,0.669591],"study_design_scores_gemma":[0.000005587542,0.00004173327,0.001659714,0.000003429,0.00001159802,0.00005859104,0.00001176282,0.9942162,0.002950591,0.0007961381,0.0002367444,0.000007801454],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1394733,0.0001801116,0.858252,0.0001414325,0.00004067715,0.00005380112,0.0001246742,0.0007769896,0.0009568672],"genre_scores_gemma":[0.8681114,0.0001541933,0.1295266,0.00009897769,0.00006842522,0.00007586603,0.0006211749,0.00003697062,0.001306441],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002384416,"threshold_uncertainty_score":0.004741073,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03617157371223183,"score_gpt":0.280573390985326,"score_spread":0.2444018172730941,"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."}}