{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001389114,0.0001399163,0.0001610544,0.0001074095,0.0001704719,0.0002623076,0.001342189,0.00008249506,0.00002843661],"category_scores_gemma":[0.00008564944,0.0001174425,0.00004943272,0.0004166795,0.00004598116,0.0003759109,0.0004602117,0.00009257181,0.0006003231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003657536,"about_ca_system_score_gemma":0.00004756519,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009154846,"about_ca_topic_score_gemma":0.00006644682,"domain_scores_codex":[0.9987684,0.0000107067,0.0002180363,0.0004678287,0.00015675,0.0003782573],"domain_scores_gemma":[0.9985731,0.0001873277,0.00005864535,0.0008390512,0.0002419289,0.00009998719],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.000001512795,0.00004078968,0.0003465239,0.00001598346,0.00001445225,6.355932e-7,0.0001273124,0.00004118412,0.0006019446,0.1811282,0.09287484,0.7248066],"study_design_scores_gemma":[0.000546171,0.0002899424,0.001055801,0.00003900738,0.000007726633,0.00001700523,0.000372581,0.08105095,0.006186211,0.05358965,0.8562809,0.0005640631],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.00192579,0.00009296279,0.981944,0.008390933,0.0001091405,0.0023545,0.000003963604,0.001394643,0.003784025],"genre_scores_gemma":[0.5161328,0.000001811639,0.4739438,0.00185993,0.00004481226,0.003765515,0.000006717986,0.00001250927,0.004232076],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.763406,"threshold_uncertainty_score":0.7716139,"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."}}