{"id":"W2003922624","doi":"10.1109/ccece.2014.6901145","title":"City traffic management model using Wireless Sensor Networks","year":2014,"lang":"en","type":"article","venue":"","topic":"Traffic control and management","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Traffic congestion; Network traffic control; Floating car data; Traffic congestion reconstruction with Kerner's three-phase theory; Vehicle Information and Communication System; Computer network; Wireless sensor network; Transport engineering; Network congestion; Scheme (mathematics); Road traffic; 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":[0.0001127233,0.0001464347,0.0001452874,0.00005798852,0.00004717326,0.00003557068,0.000113024,0.00004296666,0.00003384431],"category_scores_gemma":[6.294837e-7,0.0001386862,0.00005722484,0.00008790185,0.00001129049,0.00005487129,0.0000396022,0.00007746422,0.0000143339],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004262618,"about_ca_system_score_gemma":0.000001307581,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003346201,"about_ca_topic_score_gemma":0.00002024201,"domain_scores_codex":[0.999267,0.000009633412,0.0001545054,0.0001660549,0.0001117079,0.0002911126],"domain_scores_gemma":[0.9996789,0.00001135355,0.0000119473,0.000221714,0.000009476813,0.00006662325],"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":[0.00000273827,0.00001266924,0.000003075454,0.00003214304,0.00005740379,0.000002092921,0.00001936999,0.9060968,0.00003236171,0.002231843,0.0007839132,0.09072566],"study_design_scores_gemma":[0.0003764959,0.000005126053,0.000171411,0.00001040703,0.00005475509,8.42016e-7,0.00002207172,0.9965516,0.000006613607,0.00003339471,0.002591994,0.0001753306],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2423946,0.0000351403,0.7306477,0.00003140609,0.0002194626,0.0001521288,4.835423e-7,0.0007281355,0.025791],"genre_scores_gemma":[0.9917767,0.00003038575,0.006745759,0.0001072269,0.00009098065,0.00001000985,0.000002091795,0.00002700103,0.001209868],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.7493821,"threshold_uncertainty_score":0.565546,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01154213939591487,"score_gpt":0.1914495799649996,"score_spread":0.1799074405690848,"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."}}