{"id":"W2011705691","doi":"10.1109/vtcspring.2013.6692488","title":"ConProVA: A Smart Context Provisioning Middleware for VANET Applications","year":2013,"lang":"en","type":"article","venue":"","topic":"Peer-to-Peer Network Technologies","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"","keywords":"Computer science; Middleware (distributed applications); Vehicular ad hoc network; Provisioning; Context (archaeology); Computer security; Intelligent transportation system; Context awareness; Wireless ad hoc network; Computer network; Distributed computing; Telecommunications; Transport engineering; Phone; Engineering; Wireless","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":[0.0007281018,0.0008564147,0.0006414084,0.0005987795,0.0007489392,0.001444099,0.001936969,0.0009063291,0.002317332],"category_scores_gemma":[0.002003175,0.0006094446,0.0004380861,0.0003609374,0.0004544032,0.00214599,0.002433987,0.001380943,0.0006144462],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000547513,"about_ca_system_score_gemma":0.001006107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003281041,"about_ca_topic_score_gemma":0.003053328,"domain_scores_codex":[0.9992839,0.0001229236,0.00009485438,0.0001740875,0.0002083659,0.0001160071],"domain_scores_gemma":[0.9993168,0.0001333151,0.00008259357,0.000198958,0.0001190954,0.00014921],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003032723,0.001480944,0.02112164,0.002726032,0.0007673876,0.002658583,0.002395612,0.1084728,0.2102765,0.03325664,0.050292,0.5635192],"study_design_scores_gemma":[0.0004233556,0.0006486936,0.01000172,0.0001717396,0.0003846472,0.001706701,0.0006946087,0.7023219,0.09583123,0.01157012,0.1759425,0.000302788],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.1640564,0.003369001,0.7193567,0.001223576,0.0006757472,0.001445815,0.001164423,0.09030683,0.01840147],"genre_scores_gemma":[0.7705426,0.0009821118,0.2138346,0.0005107272,0.0001006813,0.0004199689,0.001672923,0.001187809,0.01074857],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.003281041,"threshold_uncertainty_score":0.007752299,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01608678577254328,"score_gpt":0.2379102360357051,"score_spread":0.2218234502631618,"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."}}