{"id":"W2116447947","doi":"10.1109/twc.2014.010214.122008","title":"Reliable Periodic Safety Message Broadcasting in VANETs Using Network Coding","year":2014,"lang":"en","type":"article","venue":"IEEE Transactions on Wireless Communications","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":85,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Linear network coding; Computer network; Broadcasting (networking); Coding (social sciences); Node (physics); Reliability (semiconductor); Collision; Protocol stack; Wireless sensor network; Computer security; Network packet","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0006435576,0.0003258086,0.0004108074,0.0002277318,0.0008396321,0.00009899871,0.0008269274,0.0002108046,0.0000645351],"category_scores_gemma":[0.000008742431,0.0004003955,0.0001337365,0.0009200001,0.000140287,0.0002884555,0.00001339229,0.00112039,0.00005369163],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003821942,"about_ca_system_score_gemma":0.00004713396,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001684387,"about_ca_topic_score_gemma":0.001251059,"domain_scores_codex":[0.997883,0.000259063,0.0006415301,0.0003027334,0.0002352295,0.0006784058],"domain_scores_gemma":[0.997395,0.0005003527,0.0000872356,0.001805824,0.00005852312,0.0001530025],"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":[0.00001015322,0.00007079272,0.0000992016,0.00003373288,0.00004154244,0.000002030466,0.0002752858,0.9852269,0.001357496,0.0003627441,0.00008523296,0.01243491],"study_design_scores_gemma":[0.0005014748,0.00002093734,0.0002139964,0.0004413098,0.00004878899,0.00002349884,0.00007536742,0.992899,0.0005014739,0.00006952517,0.004815687,0.0003889553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1037042,0.0006049282,0.8892097,0.0001706738,0.000623404,0.0004437682,0.0000200785,0.0006971976,0.004526046],"genre_scores_gemma":[0.9855628,0.001134049,0.0128531,0.00008189478,0.00008054611,0.0000782117,0.00002274754,0.0001111691,0.0000754735],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8818586,"threshold_uncertainty_score":0.9998448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02071985246508682,"score_gpt":0.2407248443432919,"score_spread":0.2200049918782051,"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."}}