{"id":"W4401402795","doi":"10.1007/978-3-031-67447-1_26","title":"Real-Time Traffic Management Using Feature Selection and Deep Learning in Vehicular Fog Computing","year":2024,"lang":"en","type":"book-chapter","venue":"Lecture notes in networks and systems","topic":"Traffic Prediction and Management Techniques","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"École de Technologie Supérieure","funders":"","keywords":"Feature selection; Computer science; Deep learning; Selection (genetic algorithm); Feature (linguistics); Real-time computing; 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":[0.0002793824,0.000455907,0.0005430326,0.0003194538,0.0003001604,0.0006896178,0.0007387056,0.0003507549,0.0006133783],"category_scores_gemma":[0.0004885382,0.0001788589,0.0002850743,0.0005977995,0.0002275659,0.0007781958,0.0004145982,0.0006261583,0.0001316477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005691764,"about_ca_system_score_gemma":0.0004134337,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006785335,"about_ca_topic_score_gemma":0.009148751,"domain_scores_codex":[0.9998889,0.00001569434,0.000005059027,0.00003085846,0.00002407797,0.00003547495],"domain_scores_gemma":[0.9998704,0.00004712911,0.00001124883,0.00001821842,0.00004176897,0.00001125065],"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":[0.0002303991,0.0002287018,0.002365258,0.00005901074,0.00008140229,0.000123653,0.00006788657,0.5136986,0.01616987,0.007457815,0.007842273,0.4516751],"study_design_scores_gemma":[0.000001260455,0.00001257466,0.0002493151,0.000001872424,0.000004763379,0.00001039167,0.000005916769,0.9962779,0.001019281,0.002124629,0.0002891967,0.000002856533],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.08416275,0.001130362,0.909645,0.0002299248,0.0002212028,0.00003060438,0.0001411427,0.001128415,0.003310458],"genre_scores_gemma":[0.9470532,0.0003333547,0.05048434,0.00006683416,0.00005478739,0.00001708762,0.000150002,0.00003660565,0.00180388],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006785335,"threshold_uncertainty_score":0.01349169,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005763335334814186,"score_gpt":0.1982565723139633,"score_spread":0.1924932369791492,"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."}}