{"id":"W4253435193","doi":"10.32920/ryerson.14665023","title":"Design and Analysis of an Efficient and Reliable Mac Protocol for Vanets","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Vehicular ad hoc network; Computer science; Broadcasting (networking); Computer network; Wireless; Channel (broadcasting); Wireless network; Protocol (science); Range (aeronautics); Scheme (mathematics); Wireless ad hoc network; Telecommunications; Engineering","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":[0.001857717,0.001244474,0.0008864065,0.001369563,0.0008242398,0.001904181,0.001604859,0.001020976,0.001644182],"category_scores_gemma":[0.005484282,0.0008482849,0.0009281226,0.0007798538,0.000915216,0.001537541,0.001141007,0.001290989,0.0005475419],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001539879,"about_ca_system_score_gemma":0.002565688,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003711902,"about_ca_topic_score_gemma":0.002396927,"domain_scores_codex":[0.9979218,0.0004928844,0.0001341989,0.0002660317,0.0009996081,0.0001855278],"domain_scores_gemma":[0.9981287,0.0007019829,0.0003083796,0.0001475608,0.0006680466,0.00004537915],"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":[0.00003075447,0.00003173332,0.0004507993,0.0001833204,0.00004474774,0.0001669942,0.00007088434,0.9250125,0.006985839,0.04334317,0.000972839,0.02270639],"study_design_scores_gemma":[0.00000628424,0.00006778292,0.00007398485,0.00001702892,0.00001906379,0.00005577447,0.00001857564,0.9916967,0.001338456,0.004649085,0.002046613,0.00001068478],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.006719218,0.0009618003,0.9874422,0.0002399851,0.0001000848,0.0002664162,0.00004604968,0.0002350951,0.0039892],"genre_scores_gemma":[0.6690224,0.003518258,0.3173969,0.0002655243,0.0002511106,0.001575608,0.0002579614,0.0002050301,0.007507196],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003711902,"threshold_uncertainty_score":0.01117271,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02005567310265283,"score_gpt":0.2702901838679895,"score_spread":0.2502345107653367,"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."}}