{"id":"W2971032560","doi":"10.1109/tii.2019.2938529","title":"Modeling and Analysis of a Shared Edge Caching System for Connected Cars and Industrial IoT-Based Applications","year":2019,"lang":"en","type":"article","venue":"IEEE Transactions on Industrial Informatics","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":72,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs","keywords":"Enhanced Data Rates for GSM Evolution; Computer science; Content delivery; Edge computing; Internet of Things; Distributed computing; Computer network; Embedded system; Telecommunications","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":[0.0008331406,0.0009166565,0.001163978,0.0009407986,0.0008337712,0.001819941,0.001823536,0.001822556,0.003011776],"category_scores_gemma":[0.002531473,0.0005063603,0.001052187,0.0009154232,0.001058765,0.001684744,0.001112657,0.0009255599,0.0003925631],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003199658,"about_ca_system_score_gemma":0.001921772,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03232074,"about_ca_topic_score_gemma":0.01371977,"domain_scores_codex":[0.9994169,0.000124605,0.00002815551,0.0001047588,0.0001575929,0.0001679719],"domain_scores_gemma":[0.9986567,0.0005693634,0.0002419185,0.00005466782,0.0004194769,0.00005776497],"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":[0.00002904015,0.00002370631,0.0005928474,0.00004576108,0.00001947173,0.0001324363,0.00005529034,0.9690701,0.001611852,0.02589616,0.0005808306,0.001942504],"study_design_scores_gemma":[0.000001808291,0.000004519793,0.00005543175,0.000001684757,0.00000414993,0.00001038621,0.000006969604,0.9987847,0.00005928188,0.0009779187,0.00009073514,0.000002417945],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1690221,0.002251912,0.7998576,0.001393133,0.0001412339,0.0001782766,0.0005018871,0.0005252674,0.02612863],"genre_scores_gemma":[0.9790111,0.0007138644,0.01157853,0.000112478,0.00004269492,0.0001073942,0.0001193553,0.00005611268,0.008258433],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.03232074,"threshold_uncertainty_score":0.06426519,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05300024585065749,"score_gpt":0.245725733672694,"score_spread":0.1927254878220365,"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."}}