{"id":"W2887923816","doi":"10.1155/2018/7637059","title":"A Fuzzy‐Rule Based Data Delivery Scheme in VANETs with Intelligent Speed Prediction and Relay Selection","year":2018,"lang":"en","type":"article","venue":"Wireless Communications and Mobile Computing","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Thompson Rivers University","funders":"Education Department of Henan Province","keywords":"Computer science; Relay; Computer network; Global Positioning System; Network packet; Routing protocol; Wireless; Reliability (semiconductor); Transmission delay; Transmission (telecommunications); Vehicular ad hoc network; Real-time computing; Intelligent transportation system; Wireless ad hoc network; Telecommunications","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":[0.0003550469,0.0001504218,0.0001672564,0.0001176905,0.0002482787,0.00006917876,0.0003686135,0.0000817426,0.000003543734],"category_scores_gemma":[0.000008001557,0.000155354,0.00001133565,0.0003242843,0.0001487509,0.000176423,0.0003842787,0.0003095073,0.000003224945],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006817523,"about_ca_system_score_gemma":0.00002859229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000101707,"about_ca_topic_score_gemma":0.0005862099,"domain_scores_codex":[0.9990634,0.00008154703,0.0002653126,0.0002644466,0.00009667622,0.0002286273],"domain_scores_gemma":[0.9987109,0.0001305785,0.00005487962,0.000958201,0.00007409551,0.00007139207],"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":[0.00002754583,0.0001217781,0.02470035,0.00009055434,0.00007150244,0.000002503882,0.000833763,0.8294118,0.002938161,0.00014774,0.0002067624,0.1414475],"study_design_scores_gemma":[0.0003670549,0.00008709415,0.003937115,0.0002355778,0.00001712025,0.00003161784,0.000144083,0.9923095,0.0002269317,0.000007505021,0.002482496,0.0001538732],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9771408,0.001763168,0.02012996,0.00003327035,0.00005754432,0.0003507869,0.00001186728,0.0002186494,0.0002939468],"genre_scores_gemma":[0.9807035,0.0006797488,0.01830063,0.00002412436,0.00006853334,0.00001553964,0.000171311,0.00003130766,0.000005352182],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1628977,"threshold_uncertainty_score":0.6335151,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02114885229530126,"score_gpt":0.2459702811078414,"score_spread":0.2248214288125401,"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."}}