{"id":"W2031277951","doi":"10.1145/2512921.2512923","title":"Data dissemination for delay tolerant vehicular networks","year":2013,"lang":"en","type":"article","venue":"","topic":"Opportunistic and Delay-Tolerant Networks","field":"Computer Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Computer science; Dissemination; Relay; Computer network; Network packet; Vehicular ad hoc network; Dijkstra's algorithm; Reliability (semiconductor); Path (computing); Information Dissemination; Shortest path problem; Real-time computing; Distributed computing; Wireless ad hoc network; Wireless; Telecommunications; Graph; Theoretical computer science","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":[0.0003464929,0.000140249,0.0001617935,0.00003769451,0.0001425221,0.0003110702,0.001383653,0.00009669588,0.0001199936],"category_scores_gemma":[0.000007120695,0.0001114496,0.00004667084,0.0001668851,0.00002704745,0.0009496292,0.0004304852,0.00009418158,0.00006214276],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001398076,"about_ca_system_score_gemma":0.0000339157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002583403,"about_ca_topic_score_gemma":0.000007228983,"domain_scores_codex":[0.9986723,0.00002574373,0.0002722784,0.0004886026,0.0001909217,0.0003501185],"domain_scores_gemma":[0.998155,0.0002522904,0.00007551513,0.001227311,0.0001418581,0.0001479996],"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":[0.000003705519,0.00005977123,0.00008847517,0.000008471839,0.00002282069,0.000009246296,0.00004866924,0.0008788384,0.00002433598,0.02200389,0.254854,0.7219978],"study_design_scores_gemma":[0.0001598959,0.00003691515,0.0001443678,0.00001626596,0.000009128086,0.00001461114,0.00001214072,0.9822893,0.00000890466,0.001751657,0.01538304,0.0001737531],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.0007191658,0.0001706313,0.9931017,0.001301348,0.0005113909,0.0004679537,0.000009418191,0.0001696774,0.003548756],"genre_scores_gemma":[0.9082336,0.00002475625,0.08834275,0.0008563993,0.0002622716,0.00007675079,0.0002390482,0.00001271145,0.001951661],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.9814105,"threshold_uncertainty_score":0.4544784,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0322239469368062,"score_gpt":0.275625953977129,"score_spread":0.2434020070403228,"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."}}