{"id":"W4386885133","doi":"10.1109/miot.2023.10255761","title":"Guest Editorial: Ubiquitous Intelligence for Internet of Vehicles","year":2023,"lang":"en","type":"editorial","venue":"IEEE Internet of Things Magazine","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Memorial University of Newfoundland","funders":"","keywords":"Computer science; Cloud computing; Ubiquitous computing; Edge computing; Task (project management); The Internet; Server; Drone; Resource (disambiguation); Internet of Things; Computer security; Computer network; Human–computer interaction; World Wide Web; 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":["metaepi_narrow","open_science"],"consensus_categories":[],"category_scores_codex":[0.001925473,0.0006898373,0.001350069,0.0005874363,0.00004417765,0.000270195,0.005403609,0.001094515,0.000003234265],"category_scores_gemma":[0.003091588,0.0006813692,0.0005728523,0.0005392668,0.0002333548,0.0005981021,0.001527549,0.001166159,0.0001971835],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001724689,"about_ca_system_score_gemma":0.0003460252,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006350059,"about_ca_topic_score_gemma":0.00001288819,"domain_scores_codex":[0.9946399,0.0001067659,0.001813363,0.001149255,0.00150604,0.0007847005],"domain_scores_gemma":[0.9914802,0.003895973,0.001752639,0.001082913,0.001622478,0.0001658526],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001090419,0.0001030361,0.000003789778,0.0009068313,0.0001695374,0.00001403859,0.001993285,0.00001212286,0.0007518425,0.0001736391,0.9895039,0.006258972],"study_design_scores_gemma":[0.0003637327,0.0008169251,0.00000145419,0.001731531,0.00006837159,0.000002942595,0.000008042309,0.01463082,0.02452685,0.001712708,0.9555527,0.0005839346],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.000109042,0.000135926,0.1583294,0.00008880245,0.8402548,0.0003748884,0.00001798054,0.0003659663,0.0003231736],"genre_scores_gemma":[0.000573397,0.0000583471,0.007811958,0.00002924204,0.9858057,0.00003912077,0.000122178,0.0001309183,0.005429071],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.1505174,"threshold_uncertainty_score":0.9999776,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01947600299643474,"score_gpt":0.2814082935088962,"score_spread":0.2619322905124615,"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."}}