{"id":"W4391876836","doi":"10.1109/jiot.2024.3366873","title":"Network Performance Analysis of Satellite–Terrestrial Vehicular Network","year":2024,"lang":"en","type":"article","venue":"IEEE Internet of Things Journal","topic":"Satellite Communication Systems","field":"Engineering","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo; Huawei Technologies (Canada); University of Calgary","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Low earth orbit; Satellite; Constellation; Communications satellite; Satellite constellation; Throughput; Software deployment; Computer network; Satellite system; Telecommunications; Wireless; Global Positioning System; Aerospace engineering; Engineering","routes":{"ca_aff":true,"ca_fund":true,"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":[0.001175557,0.0001755797,0.0005044525,0.0003418873,0.00003034444,0.0001263948,0.0006522018,0.0001192765,0.00009445175],"category_scores_gemma":[0.00001916507,0.00015936,0.0003782068,0.001021142,0.00005429116,0.0003382757,0.00004777167,0.0005562569,0.00002271119],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008964314,"about_ca_system_score_gemma":0.00002574083,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002411494,"about_ca_topic_score_gemma":0.000003401772,"domain_scores_codex":[0.9981328,0.0001048101,0.0009964705,0.0001282761,0.0003565568,0.0002811368],"domain_scores_gemma":[0.9990219,0.0002112819,0.0002151481,0.0003859024,0.00008281429,0.00008295778],"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":[0.00007429127,0.00001907428,0.009217327,0.0002589207,0.005167073,0.00002847422,0.003291321,0.9405423,0.002248388,0.0001572274,0.008383621,0.03061199],"study_design_scores_gemma":[0.0002325322,0.00008952631,0.002376684,0.001403893,0.0008273437,0.000118422,0.00004168604,0.9050103,0.003491113,0.0002117132,0.08592558,0.0002712508],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.905486,0.06543022,0.01657446,0.0000736975,0.0078838,0.000141443,0.000003211246,0.0002162559,0.004190906],"genre_scores_gemma":[0.9933701,0.004145676,0.00136997,0.00003304945,0.0008889937,0.000002737295,0.000005669401,0.00003627981,0.0001474926],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08788413,"threshold_uncertainty_score":0.6498511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02328447332915745,"score_gpt":0.2481086834899885,"score_spread":0.224824210160831,"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."}}