{"id":"W1000383497","doi":"10.1016/j.adhoc.2015.06.004","title":"Geo-localized content availability in VANETs","year":2015,"lang":"en","type":"article","venue":"Ad Hoc Networks","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":13,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Vehicular ad hoc network; Computer science; Replication (statistics); Variety (cybernetics); Replicate; Content delivery; Wireless ad hoc network; Intelligent transportation system; Computer network; Content (measure theory); Telecommunications; Transport engineering; Wireless; Engineering; 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":[0.001599486,0.0005943782,0.001178247,0.001381961,0.001004823,0.001708413,0.001651299,0.00102817,0.001396418],"category_scores_gemma":[0.008993848,0.0007028865,0.0002931349,0.00252529,0.001073044,0.004021086,0.001693995,0.0007070646,0.0003433879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001086813,"about_ca_system_score_gemma":0.001015963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005433809,"about_ca_topic_score_gemma":0.005347132,"domain_scores_codex":[0.998502,0.0004104678,0.00009731138,0.0003191222,0.0004111217,0.0002598739],"domain_scores_gemma":[0.9943449,0.003249894,0.0007212517,0.0006337168,0.0008582998,0.0001918892],"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":[0.0005120568,0.00008180883,0.007030641,0.0003341977,0.0001051603,0.00088335,0.0003018109,0.8716616,0.007062838,0.04133438,0.004757946,0.06593415],"study_design_scores_gemma":[0.00001043932,0.00006247272,0.001454372,0.00002283879,0.00003911001,0.0002911382,0.00035442,0.9731621,0.002434549,0.01980932,0.002337065,0.00002215398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2065836,0.006786654,0.77132,0.001646586,0.0004876493,0.0001566496,0.001154372,0.001308812,0.01055561],"genre_scores_gemma":[0.9896731,0.0007201167,0.008273195,0.00004400489,0.0001106539,0.00002078717,0.0001993772,0.00003541106,0.0009233304],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005433809,"threshold_uncertainty_score":0.01080436,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03474792473028585,"score_gpt":0.2218418489156433,"score_spread":0.1870939241853575,"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."}}