{"id":"W3161886122","doi":"10.1109/tgcn.2021.3080918","title":"A Novel Joint Optimization Method Based on Mobile Data Collection for Wireless Rechargeable Sensor Networks","year":2021,"lang":"en","type":"article","venue":"IEEE Transactions on Green Communications and Networking","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa","funders":"Canada Research Chairs","keywords":"Computer science; Data collection; Network packet; Wireless sensor network; Cluster analysis; Energy consumption; Efficient energy use; Scheduling (production processes); Wireless; Real-time computing; Computer network; Distributed computing; Engineering; Electrical engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005791676,0.0002743735,0.0003169152,0.0001567352,0.000887709,0.0001290491,0.0004483072,0.0002330812,0.00001728049],"category_scores_gemma":[0.000002977364,0.0003230958,0.00008836002,0.0007964715,0.00005887672,0.0001766429,0.0000172626,0.0005659016,0.000001003748],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001277779,"about_ca_system_score_gemma":0.0000552141,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00009138454,"about_ca_topic_score_gemma":0.0003956307,"domain_scores_codex":[0.9984078,0.0001874905,0.000438922,0.0004582363,0.0001509861,0.0003565653],"domain_scores_gemma":[0.9963588,0.001230604,0.0001005638,0.002048882,0.0001545368,0.0001066826],"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":[0.00002313749,0.0001334359,0.000003922164,0.00003084835,0.00006991417,6.085114e-7,0.00003161446,0.86549,0.0003299404,0.00001443914,0.0002371971,0.133635],"study_design_scores_gemma":[0.0006652598,0.00008469749,0.000003047594,0.0003313249,0.0001027553,0.00001668194,0.00003229146,0.9921876,0.0006890353,0.000009804094,0.005561148,0.000316421],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.0001155148,0.0007266879,0.9968303,0.0002434423,0.0007460334,0.0004515877,0.00007484767,0.0003994697,0.0004121498],"genre_scores_gemma":[0.3796274,0.004526848,0.6137323,0.0003090459,0.0002718483,0.0006268923,0.0004602899,0.0001466907,0.0002986218],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.3830979,"threshold_uncertainty_score":0.9999221,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07138969259166522,"score_gpt":0.2836555669995921,"score_spread":0.2122658744079269,"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."}}