{"id":"W4406158156","doi":"10.1109/tits.2024.3520487","title":"Knowledge Guided Visual Transformers for Intelligent Transportation Systems","year":2025,"lang":"en","type":"article","venue":"IEEE Transactions on Intelligent Transportation Systems","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Brandon University","funders":"Norges Forskningsråd; The Research Council","keywords":"Computer science; Intelligent transportation system; Robustness (evolution); Cluster analysis; Crash; Artificial intelligence; Machine learning; Intelligent decision support system; Engineering; 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":[0.0009981804,0.000696692,0.0005904594,0.0007460432,0.0003705547,0.001457812,0.001511078,0.0008649127,0.003329647],"category_scores_gemma":[0.003733774,0.0002586922,0.0006269861,0.0007345984,0.001046384,0.003175338,0.001757718,0.001253363,0.0006872094],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001338635,"about_ca_system_score_gemma":0.001196694,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003828529,"about_ca_topic_score_gemma":0.003139805,"domain_scores_codex":[0.999376,0.0001995522,0.00003413246,0.0001330428,0.0001849447,0.00007233495],"domain_scores_gemma":[0.9991165,0.0002588275,0.0000765916,0.0003036326,0.0001843482,0.00006004204],"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":[0.0002422135,0.0001208917,0.001217082,0.000103603,0.00005368642,0.0001160088,0.0001379136,0.6310683,0.008061823,0.04414327,0.004128088,0.310607],"study_design_scores_gemma":[0.000009735965,0.0000498417,0.0001273998,0.00000690386,0.000008074833,0.00004149203,0.00002686941,0.9573502,0.003462085,0.03752051,0.001389595,0.000007277174],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.02081972,0.0001903222,0.9731234,0.0002433559,0.00003090543,0.00004715159,0.0001120791,0.002320403,0.003112663],"genre_scores_gemma":[0.8889692,0.0001618312,0.1082258,0.0001462417,0.0000240729,0.00004713235,0.000275339,0.0001351178,0.00201516],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003828529,"threshold_uncertainty_score":0.01113874,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04017425846132747,"score_gpt":0.3325778009963161,"score_spread":0.2924035425349886,"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."}}