{"id":"W4417509118","doi":"10.1109/icsit65336.2025.11294554","title":"Advanced Detection of Helmet Usage and Number Plates in Riders","year":2025,"lang":"","type":"article","venue":"","topic":"Advanced Neural Network Applications","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"","keywords":"Law enforcement; Object detection; Human error; Data collection; Object (grammar); Automation","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":[0.0001573459,0.0006262515,0.0003840679,0.001413918,0.0001432069,0.0003900543,0.0006052966,0.0005303452,0.003638197],"category_scores_gemma":[0.0006959129,0.0002393249,0.0003994059,0.0004458527,0.0001822434,0.0004546191,0.0005822722,0.0003288485,0.002279639],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002616267,"about_ca_system_score_gemma":0.0002693076,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.009708357,"about_ca_topic_score_gemma":0.02864089,"domain_scores_codex":[0.9997305,0.00002380794,0.00001276717,0.0001153436,0.0000599173,0.00005763613],"domain_scores_gemma":[0.9997215,0.00003420194,0.00004862676,0.00003227009,0.0001296046,0.00003373797],"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":[0.001156024,0.0003581253,0.2321949,0.001286816,0.0002554534,0.001245343,0.0005855066,0.009797608,0.1165368,0.0006928399,0.03333322,0.6025572],"study_design_scores_gemma":[0.00006356217,0.0007735998,0.6105264,0.0004758628,0.0002455281,0.003559786,0.001762015,0.231886,0.116409,0.001050126,0.03306303,0.0001851234],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9022548,0.001952534,0.05588278,0.0003588505,0.0003482461,0.000271162,0.01282189,0.005761887,0.02034791],"genre_scores_gemma":[0.9269832,0.0006359014,0.04757149,0.0002194224,0.00007579753,0.0001013511,0.01116705,0.0001742191,0.0130716],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009708357,"threshold_uncertainty_score":0.01930368,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009549717358566403,"score_gpt":0.2761873870102191,"score_spread":0.2666376696516526,"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."}}