{"id":"W2997386769","doi":"10.48550/arxiv.1912.13203","title":"Modeling and Analysis of Energy Harvesting and Smart Grid-Powered Wireless Communication Networks: A Contemporary Survey","year":2019,"lang":"en","type":"preprint","venue":"arXiv (Cornell University)","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Science and Technology Commission of Shanghai Municipality; Natural Sciences and Engineering Research Council of Canada; Fudan University; National Natural Science Foundation of China","keywords":"Smart grid; Computer science; Wireless; Energy harvesting; Energy consumption; Renewable energy; Computer network; Distributed computing; Telecommunications; Energy (signal processing); Engineering; Electrical engineering","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":[0.0004936692,0.0009559373,0.0009761871,0.0008008276,0.0002797348,0.001461204,0.001084043,0.001322562,0.002051759],"category_scores_gemma":[0.000988497,0.0003998396,0.0006274822,0.002040339,0.0006817238,0.001837043,0.0007208858,0.001276366,0.0007809909],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006703684,"about_ca_system_score_gemma":0.0005779702,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002268275,"about_ca_topic_score_gemma":0.001290918,"domain_scores_codex":[0.9996378,0.0001062113,0.00002704467,0.00006698947,0.0001347854,0.00002711419],"domain_scores_gemma":[0.9996315,0.0002110959,0.00005080603,0.00002305755,0.00007359553,0.000009874864],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00005970437,0.0001152407,0.002351421,0.002665313,0.000105928,0.0004123744,0.0002394624,0.4169898,0.003694296,0.282324,0.02021105,0.2708313],"study_design_scores_gemma":[0.000008308263,0.00007821414,0.001248801,0.0005435419,0.00004591281,0.0003512491,0.0001199119,0.7406489,0.0008332946,0.1573327,0.09873393,0.00005532241],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.01025997,0.3061002,0.6434256,0.004041588,0.000900476,0.0001013923,0.0005232531,0.0002687052,0.03437879],"genre_scores_gemma":[0.2282287,0.6847606,0.06103724,0.0009685322,0.003767273,0.0004584588,0.000980221,0.0001419848,0.01965698],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.002268275,"threshold_uncertainty_score":0.006863832,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06121291284677916,"score_gpt":0.1805051028614764,"score_spread":0.1192921900146973,"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."}}