{"id":"W4310130661","doi":"10.1016/j.vehcom.2022.100551","title":"Autonomous vehicles in 5G and beyond: A survey","year":2022,"lang":"en","type":"article","venue":"Vehicular Communications","topic":"Vehicular Ad Hoc Networks (VANETs)","field":"Engineering","cited_by":212,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of New Brunswick","funders":"Horizon 2020 Framework Programme; European Commission","keywords":"Computer science; Emerging technologies; Mobile broadband; Telecommunications; Broadband; Low latency (capital markets); Cellular network; Automation; Systems engineering; Computer security; Wireless; Computer network; 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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0008056107,0.0001504017,0.000198841,0.0001694259,0.0003307876,0.00004448865,0.0007680639,0.00005653342,0.00004410135],"category_scores_gemma":[0.00003340633,0.000188114,0.00004529661,0.0005582579,0.00008746033,0.00009822282,0.0005432736,0.0006378628,0.00001820955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001811329,"about_ca_system_score_gemma":0.00003887934,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004214663,"about_ca_topic_score_gemma":0.002124239,"domain_scores_codex":[0.9986122,0.0004619691,0.0002817269,0.0001798445,0.0001676062,0.0002966117],"domain_scores_gemma":[0.998242,0.000237193,0.0000341849,0.001378027,0.00002569544,0.00008288827],"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":[0.000005004114,0.0001137644,0.01271512,0.00001542034,0.00006016098,0.00001734486,0.00078309,0.9716246,0.0008062774,0.001977388,0.001655054,0.01022684],"study_design_scores_gemma":[0.0003789985,0.00002129112,0.1077432,0.000008306271,0.00001376294,0.00004283412,0.0001888843,0.8329774,0.00003729346,0.000426789,0.05788666,0.000274619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9797938,0.01383439,0.0002481861,0.0009392699,0.0001240787,0.0004232757,0.00009261842,0.00040767,0.004136693],"genre_scores_gemma":[0.9971779,0.0006248649,0.001440348,0.0001513344,0.00001169737,0.0002361723,0.000250016,0.00004782939,0.00005984482],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1386472,"threshold_uncertainty_score":0.7671066,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01839727622504556,"score_gpt":0.2285177590632034,"score_spread":0.2101204828381578,"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."}}