{"id":"W3048175825","doi":"10.1007/978-3-030-51229-3_6","title":"Link-Aware Reliable Beaconing Scheme Design","year":2020,"lang":"en","type":"book-chapter","venue":"Wireless networks","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"","keywords":"Computer science; Beacon; Link (geometry); Markov chain; Reliability (semiconductor); Non-line-of-sight propagation; Broadcasting (networking); Computer network; Scheme (mathematics); Wireless; Real-time computing; Telecommunications; Machine learning","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","research_integrity"],"consensus_categories":["research_integrity"],"category_scores_codex":[0.0002848942,0.001138748,0.001223883,0.0001407603,0.0001804222,0.000176006,0.0007319589,0.001784022,0.0004636428],"category_scores_gemma":[0.000008701497,0.001328818,0.000394458,0.0001476653,0.000107413,0.0001631548,0.0002305695,0.003091985,0.0006491218],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003125692,"about_ca_system_score_gemma":0.00009580953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004829379,"about_ca_topic_score_gemma":0.00001051823,"domain_scores_codex":[0.9966506,0.00003191946,0.000814324,0.0008989464,0.0005135801,0.00109066],"domain_scores_gemma":[0.9980574,0.0001774956,0.0002110712,0.0009383563,0.0001101701,0.000505464],"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":[0.00002093934,0.000003616543,0.000004052535,0.0001421349,0.0003484956,0.0003076326,0.00003179385,0.9175091,0.00001917077,0.005324346,0.06448324,0.01180544],"study_design_scores_gemma":[0.0003235836,0.00004604456,0.000001509709,0.001007239,0.0001251468,0.00002894381,0.000003519028,0.7863641,0.00002637632,0.000646458,0.2103593,0.001067763],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.00003310872,0.02684011,0.6542355,0.0002531295,0.003414062,0.001564429,0.00004030711,0.004317268,0.3093021],"genre_scores_gemma":[0.3148242,0.03697803,0.04594252,0.003584558,0.0516922,0.0006360789,0.004394742,0.009148166,0.5327995],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.6082929,"threshold_uncertainty_score":0.9995119,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01623897801659311,"score_gpt":0.1874665419983527,"score_spread":0.1712275639817596,"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."}}