{"id":"W2798337874","doi":"10.1109/access.2018.2824839","title":"Drone-Based Highway-VANET and DAS Service","year":2018,"lang":"en","type":"article","venue":"IEEE Access","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":61,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Drone; Vehicular ad hoc network; Computer science; Computer network; Network packet; Wireless ad hoc network; Probabilistic logic; Wireless; Telecommunications; Artificial intelligence","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003082543,0.0005373821,0.0004936631,0.0006156617,0.0004631664,0.0009538856,0.001011492,0.0005782535,0.003331436],"category_scores_gemma":[0.001063324,0.0001858192,0.0003682216,0.0009814631,0.0003564995,0.00126103,0.00129131,0.0005830973,0.000881473],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006758245,"about_ca_system_score_gemma":0.0007961846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003760107,"about_ca_topic_score_gemma":0.005184288,"domain_scores_codex":[0.9995758,0.0001055899,0.00002387499,0.00009234103,0.0001148441,0.0000876198],"domain_scores_gemma":[0.9995702,0.0001008866,0.00006022412,0.00008219769,0.0001408371,0.00004571784],"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":[0.0002820104,0.0001456128,0.003903223,0.000537964,0.000131723,0.0005846396,0.0001839448,0.644553,0.01245841,0.1603577,0.008748673,0.168113],"study_design_scores_gemma":[0.00001844872,0.0001816103,0.0006484176,0.00001999948,0.000024479,0.0004997569,0.0001522155,0.9551364,0.004469791,0.01335925,0.02545997,0.00002957001],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1565288,0.003811533,0.78289,0.0007422952,0.0004813625,0.0003201122,0.001239426,0.001554545,0.05243186],"genre_scores_gemma":[0.9536228,0.001173579,0.03319296,0.0001249858,0.00004916386,0.0000915868,0.0007551914,0.00004286614,0.0109469],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003760107,"threshold_uncertainty_score":0.0111447,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01597646052174975,"score_gpt":0.274707217464582,"score_spread":0.2587307569428323,"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."}}