{"id":"W3197054949","doi":"10.1109/tvt.2021.3109868","title":"Repair Delay Analysis of Mobile Storage Systems Using Erasure Codes and Relay Cooperation","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"Caching and Content Delivery","field":"Computer Science","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"National Natural Science Foundation of China","keywords":"Erasure; Relay; Erasure code; Computer science; Data loss; Reliability (semiconductor); Computer network; Base station; Path loss; Mobile device; Decoding methods; Real-time computing; Reliability engineering; Engineering; Telecommunications; Wireless","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001344524,0.0009610686,0.0006945198,0.001253328,0.0005626032,0.0009745084,0.001029747,0.0007962927,0.002079481],"category_scores_gemma":[0.006144274,0.0004194707,0.0006122388,0.001031606,0.001041588,0.001283362,0.0008273327,0.0008373692,0.0002641804],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003241699,"about_ca_system_score_gemma":0.001527633,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01062362,"about_ca_topic_score_gemma":0.003661452,"domain_scores_codex":[0.9993673,0.0001413606,0.00003226604,0.0001070661,0.000161951,0.000190104],"domain_scores_gemma":[0.9941401,0.003836371,0.0007234787,0.0001813367,0.0009375511,0.0001810986],"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":[0.000157286,0.00002026121,0.000775623,0.0001229982,0.00002792689,0.0001443091,0.0001314564,0.9693159,0.004224122,0.01920658,0.0005336506,0.005339928],"study_design_scores_gemma":[0.000004034373,0.00003464263,0.0001658413,0.000006851608,0.00001095818,0.00003716357,0.00004248051,0.9966509,0.0007447606,0.002121677,0.0001730781,0.00000767553],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.302653,0.004612043,0.6833117,0.0006635328,0.0001104124,0.0001065102,0.0002668034,0.0003374783,0.00793846],"genre_scores_gemma":[0.9886192,0.0008838776,0.008246553,0.00003398196,0.00002476391,0.00003692368,0.00005526422,0.00003509148,0.002064475],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01062362,"threshold_uncertainty_score":0.02352029,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01257336653552188,"score_gpt":0.2327537328803898,"score_spread":0.2201803663448679,"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."}}