{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003004192,0.0003998082,0.0003235087,0.001060863,0.0002699551,0.001269573,0.0005060203,0.0006413562,0.001368377],"category_scores_gemma":[0.000763178,0.0002033058,0.0003451392,0.0008963631,0.000365487,0.001578257,0.0004207192,0.0004315239,0.0004531129],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004544911,"about_ca_system_score_gemma":0.0003879076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001705087,"about_ca_topic_score_gemma":0.001512402,"domain_scores_codex":[0.9995727,0.00007528631,0.00001730878,0.00009392112,0.0002080032,0.00003271125],"domain_scores_gemma":[0.9997811,0.00007457675,0.00002765452,0.00002132358,0.00008495159,0.00001043985],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0002443329,0.0001961804,0.008921776,0.0007594719,0.0001523939,0.0002387801,0.0003666996,0.09479456,0.07765012,0.0670801,0.007400991,0.7421945],"study_design_scores_gemma":[0.00003344071,0.0005013893,0.01604319,0.0002700595,0.0001418346,0.0004954272,0.0006584415,0.7205088,0.06629825,0.07700747,0.1178914,0.0001503457],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0797789,0.01602613,0.8528038,0.001364311,0.000791855,0.0001386655,0.0005337623,0.001410948,0.04715161],"genre_scores_gemma":[0.9093751,0.006680182,0.07282957,0.0002152567,0.0002536042,0.00007105248,0.0004081817,0.00004585367,0.01012124],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001705087,"threshold_uncertainty_score":0.004577637,"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."}}