{"id":"W4400728238","doi":"10.1109/iwcmc61514.2024.10592467","title":"Real-Time Binary Cell Phone Usage Detection and Classification on Vehicular Edge Devices","year":2024,"lang":"en","type":"article","venue":"","topic":"Green IT and Sustainability","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Phone; Enhanced Data Rates for GSM Evolution; Binary number; Artificial intelligence","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":[0.0001398994,0.0003925566,0.0003512077,0.000519051,0.0001513769,0.0004175484,0.0003728487,0.0004143021,0.001258901],"category_scores_gemma":[0.0006775177,0.00009651035,0.0001789749,0.0004514217,0.0001053458,0.0003145714,0.0002706848,0.000216256,0.0007825643],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002219886,"about_ca_system_score_gemma":0.0001450032,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003601609,"about_ca_topic_score_gemma":0.004439749,"domain_scores_codex":[0.999801,0.00002780035,0.000009712657,0.00004730911,0.00006150179,0.00005279479],"domain_scores_gemma":[0.9997876,0.00006291074,0.00002570141,0.00002414709,0.00007869351,0.00002089952],"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":[0.00437476,0.0008886846,0.1483882,0.0003998391,0.0001597232,0.001980944,0.000318812,0.1504643,0.1020738,0.002155439,0.01550019,0.5732954],"study_design_scores_gemma":[0.00001842906,0.0002820178,0.04793641,0.00001829705,0.00002175777,0.0003256084,0.0002291624,0.917845,0.03143646,0.0005657216,0.00128889,0.00003220015],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9674579,0.0001739646,0.02655234,0.0001431513,0.00009221691,0.00002830954,0.0007037421,0.0008118784,0.004036461],"genre_scores_gemma":[0.9930426,0.00005295014,0.005136589,0.0000366448,0.000007716718,0.00001135975,0.0005722131,0.000008777716,0.00113126],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003601609,"threshold_uncertainty_score":0.007161319,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008604350242116041,"score_gpt":0.2113539467515207,"score_spread":0.2027495965094046,"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."}}