{"id":"W4290996079","doi":"10.1109/icc45855.2022.9838931","title":"UAV-assisted Wireless Power Charging for Efficient Hybrid Coded Edge Computing Network","year":2022,"lang":"en","type":"article","venue":"ICC 2022 - IEEE International Conference on Communications","topic":"UAV Applications and Optimization","field":"Engineering","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia Hospital","funders":"National Research Foundation; Ministry of Education","keywords":"Computer science; Server; Edge computing; Enhanced Data Rates for GSM Evolution; Computation; Mobile edge computing; Computation offloading; Edge device; Wireless; Quality of service; Wireless network; Distributed computing; Computer network; Wireless sensor network; Cloud computing; Artificial intelligence; Telecommunications; Algorithm","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":[],"consensus_categories":[],"category_scores_codex":[0.0003535929,0.0001823442,0.0001789196,0.0001659072,0.0009168292,0.000120212,0.001394195,0.00003460724,0.0005072539],"category_scores_gemma":[0.00001882405,0.0002252098,0.00009964105,0.0003229488,0.00006246615,0.00006786745,0.0002960392,0.0004023004,0.00003060342],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003377348,"about_ca_system_score_gemma":0.00006016585,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000152191,"about_ca_topic_score_gemma":0.00002015271,"domain_scores_codex":[0.9986514,0.00008593439,0.0004205607,0.0002588714,0.0003188878,0.0002642859],"domain_scores_gemma":[0.9983646,0.0002890516,0.0001475105,0.0008910371,0.0002420174,0.00006573847],"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":[0.00002576936,0.0002424448,0.0000708186,0.000009719572,0.0001105978,7.771642e-7,0.0004613978,0.8490426,0.002402683,0.1322774,0.008902051,0.006453745],"study_design_scores_gemma":[0.0004121873,0.00003441729,0.0003309973,0.00003068338,0.0000154253,0.000008472845,0.0003220712,0.9722179,0.0001945022,0.0005482371,0.0256517,0.0002334398],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1523467,0.0004460611,0.7540045,0.006930233,0.004802598,0.002328669,0.001551371,0.001315458,0.07627436],"genre_scores_gemma":[0.9912584,0.0001013203,0.006254008,0.0002259711,0.0001077135,0.0007288766,0.0009944489,0.00004819036,0.0002810716],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.8389117,"threshold_uncertainty_score":0.9183788,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05307691833728918,"score_gpt":0.2999803933192891,"score_spread":0.2469034749819999,"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."}}