{"id":"W3040346066","doi":"10.1109/tvt.2020.3005406","title":"Mobile Edge Computing via Wireless Power Transfer Over Multiple Fading Blocks: An Optimal Stopping Approach","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Vehicular Technology","topic":"IoT and Edge/Fog Computing","field":"Computer Science","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Natural Science Foundation of China","keywords":"Fading; Computer science; Base station; Energy harvesting; Wireless; Enhanced Data Rates for GSM Evolution; Efficient energy use; Energy (signal processing); Real-time computing; Channel (broadcasting); Computer network; Telecommunications; Engineering; Electrical engineering; Mathematics","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":[0.001235794,0.001276109,0.001355493,0.0004888095,0.0005155111,0.001355427,0.00132733,0.0009966571,0.002376731],"category_scores_gemma":[0.002367824,0.0006115186,0.0008091592,0.0006099603,0.001086088,0.001565972,0.001181751,0.001136488,0.0003204238],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009699488,"about_ca_system_score_gemma":0.0008458215,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001227535,"about_ca_topic_score_gemma":0.0009563007,"domain_scores_codex":[0.9993247,0.0002529061,0.00003209673,0.000130918,0.0001215939,0.0001378922],"domain_scores_gemma":[0.9989527,0.0006610471,0.0001050666,0.00006717467,0.0001250182,0.00008894796],"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":[0.0001067271,0.00006087461,0.0003334909,0.0000841354,0.00004537315,0.0001094132,0.00005103406,0.947017,0.004194568,0.02621273,0.0008109628,0.0209737],"study_design_scores_gemma":[0.000007512174,0.00004216317,0.00004099703,0.000004819051,0.000007429138,0.00001615197,0.00000669426,0.9912815,0.000672383,0.007550043,0.0003654395,0.000004927346],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.01154391,0.0002666325,0.985195,0.0001926666,0.00003066731,0.00003226522,0.00002001602,0.00009715455,0.002621699],"genre_scores_gemma":[0.7688638,0.0009169255,0.221988,0.0002722609,0.0001212362,0.0002011653,0.0001031861,0.0002204867,0.007312966],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002376731,"threshold_uncertainty_score":0.007950962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01505551103643797,"score_gpt":0.2291582179949982,"score_spread":0.2141027069585602,"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."}}