{"id":"W4385625740","doi":"10.1109/icaeca56562.2023.10199402","title":"Vehicle Detection and Traffic Control Using Sensor Technology","year":2023,"lang":"en","type":"article","venue":"","topic":"Autonomous Vehicle Technology and Safety","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"FPInnovations","funders":"","keywords":"Computer science; Automotive engineering; Embedded system; Real-time computing; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006882961,0.00007879102,0.0001058951,0.0002185562,0.0001057111,0.000008450921,0.00004552931,0.0002104108,0.0000129551],"category_scores_gemma":[0.00001010567,0.00007946128,0.00001592931,0.0003900944,0.0000850104,0.00004488443,0.00001518152,0.0001540451,0.00005651296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002531961,"about_ca_system_score_gemma":0.000004620905,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000002535072,"about_ca_topic_score_gemma":0.00001541357,"domain_scores_codex":[0.9995545,0.000005845308,0.0001009869,0.0001114701,0.00003009584,0.0001970633],"domain_scores_gemma":[0.9998278,0.00002319927,0.000008864057,0.0001089593,0.000009449864,0.0000217491],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00001638467,0.00001181718,0.002278009,0.00004093279,0.00009666821,0.00004264863,0.00009942314,0.2057627,0.4903448,0.001922441,0.00004428806,0.29934],"study_design_scores_gemma":[0.0003503503,0.00002091459,0.001834166,0.000002926253,0.00001013252,0.00003439682,0.0001416721,0.9770492,0.01966975,0.0002953943,0.0004879648,0.0001031295],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9793041,0.00008122874,0.01526522,0.0002155604,0.00008252943,0.00008879526,0.000001654326,0.004746885,0.0002140711],"genre_scores_gemma":[0.9994565,0.00002175095,0.0004148559,0.00001738391,0.0000153993,0.000007209766,3.71466e-7,0.00001731422,0.00004923119],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7712865,"threshold_uncertainty_score":0.3240337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007220568318182968,"score_gpt":0.1992299510877782,"score_spread":0.1920093827695952,"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."}}