{"id":"W2785955323","doi":"10.1109/vtcfall.2017.8288306","title":"Analysis of a Location-Aware Probabilistic Strategy for Opportunistic Vehicle-to-Vehicle Relay","year":2017,"lang":"en","type":"article","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of New Brunswick","funders":"","keywords":"Relay; Computer science; Computer network; Vehicle-to-vehicle; Probabilistic logic; Transmission (telecommunications); Key (lock); Stochastic geometry; Scheme (mathematics); Vehicular ad hoc network; Complement (music); Wireless; Real-time computing; Wireless ad hoc network; Telecommunications; Computer security","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":[0.001229101,0.0009878767,0.0009738063,0.0008336493,0.000572519,0.001064116,0.00149185,0.001043137,0.002354447],"category_scores_gemma":[0.00509121,0.0006585747,0.0007989602,0.000588953,0.001188965,0.001395001,0.001053193,0.000731157,0.0003226238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001967397,"about_ca_system_score_gemma":0.001549083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006444633,"about_ca_topic_score_gemma":0.003922654,"domain_scores_codex":[0.9993775,0.0001772347,0.00002062375,0.000105726,0.0001839578,0.00013498],"domain_scores_gemma":[0.9975177,0.001583244,0.0003949892,0.00008276148,0.0003347544,0.00008652741],"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":[0.00002121062,0.00001464734,0.0003339185,0.00003144253,0.00001827204,0.0001014259,0.00004284148,0.9731833,0.001037504,0.02182457,0.0003692371,0.003021617],"study_design_scores_gemma":[0.00000249544,0.00001859599,0.00008332199,0.000003024229,0.000006720311,0.00003398264,0.0000140481,0.9968327,0.0001343743,0.002690261,0.0001745789,0.00000584566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03340813,0.000461406,0.9557543,0.0004070203,0.00004759511,0.00009643072,0.00008417625,0.0001218629,0.009618981],"genre_scores_gemma":[0.9759274,0.0005272854,0.01855106,0.00007209017,0.00003663358,0.0001021277,0.00004650995,0.00004017193,0.004696725],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.006444633,"threshold_uncertainty_score":0.01427454,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03388780709875455,"score_gpt":0.2776047508179846,"score_spread":0.2437169437192301,"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."}}