{"id":"W3024137225","doi":"10.1109/tvt.2020.2994181","title":"Smart Proactive Caching: Empower the Video Delivery for Autonomous Vehicles in ICN-Based Networks","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":82,"is_retracted":false,"has_abstract":true,"ca_institutions":"Carleton University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Computer science; Cache; Quality of experience; Computer network; Augmented reality; Popularity; Multimedia; Quality of service; Human–computer interaction","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":[0.0002445787,0.0002393399,0.0002690476,0.0002960753,0.00033967,0.00008080316,0.0009669906,0.0002913487,0.000003343426],"category_scores_gemma":[0.00002008824,0.0001989781,0.0002140565,0.0008267739,0.0001360341,0.0001840425,0.000009678284,0.000848971,0.00001608355],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001162199,"about_ca_system_score_gemma":0.000125093,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009519277,"about_ca_topic_score_gemma":0.0001017821,"domain_scores_codex":[0.9983799,0.0001068559,0.0003015739,0.0006179175,0.0001756979,0.0004180441],"domain_scores_gemma":[0.9989029,0.0002467498,0.00008500864,0.0006028758,0.00008824839,0.00007418906],"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":[0.0002480776,0.0004484795,0.000184729,0.00002365569,0.0001880698,0.00008678915,0.0005122219,0.8559712,0.007569443,0.002449266,0.000307397,0.1320107],"study_design_scores_gemma":[0.0009557924,0.000407019,0.00008304697,0.00002850985,0.00003546206,0.0000149099,0.0001086741,0.9801821,0.015622,0.0002961722,0.002000047,0.0002662896],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1161568,0.0001762036,0.8639748,0.01814524,0.0003144009,0.0006181398,0.000007831045,0.0005817006,0.00002491075],"genre_scores_gemma":[0.995263,0.0000141922,0.001706744,0.002587551,0.00003002007,0.000346623,0.000001901513,0.0000235419,0.00002642613],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8791062,"threshold_uncertainty_score":0.8114093,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01667388066321698,"score_gpt":0.2186177178035112,"score_spread":0.2019438371402942,"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."}}