{"id":"W2048883805","doi":"10.1109/tvt.2012.2227071","title":"Downlink Traffic Scheduling in Green Vehicular Roadside Infrastructure","year":2012,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Computer science; Scheduling (production processes); Mathematical optimization; Job shop scheduling; Dynamic priority scheduling; Telecommunications link; Schedule; Real-time computing; Computer network; Mathematics","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003155798,0.0005584615,0.0005762985,0.001190297,0.0001587909,0.00003125497,0.0004994345,0.00119103,0.0001230778],"category_scores_gemma":[0.00001030626,0.0005972641,0.0002366604,0.001636399,0.0001718797,0.0003439831,0.000005847846,0.002121139,0.000259966],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003999678,"about_ca_system_score_gemma":0.00004014324,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002043093,"about_ca_topic_score_gemma":0.0001835663,"domain_scores_codex":[0.9971956,0.00007891848,0.0005934024,0.0004786258,0.0003476882,0.001305759],"domain_scores_gemma":[0.9987479,0.00005571386,0.00006462538,0.0008431029,0.00005463724,0.000233996],"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":[0.00001250523,0.00010773,0.0002705483,0.00003847134,0.0001289581,0.00006734381,0.0001368938,0.9534757,0.007423289,0.00009403779,0.00004782933,0.03819676],"study_design_scores_gemma":[0.001097761,0.0000852805,0.0006441959,0.000130018,0.0001016389,0.0003280336,0.0001544151,0.9579523,0.03282174,0.0002251227,0.005675625,0.0007839102],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8834993,0.001775974,0.1110492,0.0003786692,0.0009230336,0.0004817609,0.0000108467,0.001761032,0.0001201709],"genre_scores_gemma":[0.9945211,0.0002266586,0.004600105,0.0001155596,0.0001657229,0.0001733073,0.00001251064,0.00014489,0.00004011423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1110218,"threshold_uncertainty_score":0.9996479,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005924881663470849,"score_gpt":0.2047763333507064,"score_spread":0.1988514516872355,"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."}}