{"id":"W2411777060","doi":"10.1109/access.2016.2579598","title":"Cooperative Wireless Energy Harvesting and Spectrum Sharing in 5G Networks","year":2016,"lang":"en","type":"article","venue":"IEEE Access","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":84,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"Fundamental Research Funds for the Central Universities; China Scholarship Council; China Postdoctoral Science Foundation; National Natural Science Foundation of China","keywords":"Computer science; Energy harvesting; Relay; Wireless; Energy (signal processing); Throughput; Computer network; Wireless sensor network; Data transmission; Transfer (computing); Mechanism (biology); Telecommunications","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":[0.0001959802,0.0002831443,0.0003035583,0.0001419619,0.00008489755,0.0002328841,0.0004779421,0.0001647084,0.00002246594],"category_scores_gemma":[0.00003591058,0.0002358521,0.00002852287,0.0004104253,0.00008930323,0.000867106,0.000116184,0.0002370568,0.000003480923],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001141127,"about_ca_system_score_gemma":0.00001369065,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004642454,"about_ca_topic_score_gemma":0.002635419,"domain_scores_codex":[0.9984689,0.00004127651,0.0003575491,0.0004219678,0.0001312177,0.000579108],"domain_scores_gemma":[0.9991673,0.0003111361,0.00005655782,0.0003050451,0.00002924785,0.0001307334],"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":[0.00001275476,0.00001723334,0.04122671,0.00003799802,0.0000424622,0.00008316992,0.00008039304,0.8847919,0.003303015,0.004274901,0.0003530475,0.06577643],"study_design_scores_gemma":[0.001029244,0.00003121488,0.02362151,0.001162486,0.00001357212,0.00003351134,0.00001246921,0.9472826,0.02440697,0.0007917084,0.000782795,0.0008319184],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8629758,0.0005174397,0.1303054,0.00008243434,0.0009223255,0.00008520618,0.000002865418,0.0005096654,0.004598811],"genre_scores_gemma":[0.9982037,0.0005119578,0.0001144936,0.0000784771,0.000528567,0.0000480028,0.00000247892,0.00008863387,0.0004236785],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1352279,"threshold_uncertainty_score":0.9617769,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01449288264028439,"score_gpt":0.2287222270711662,"score_spread":0.2142293444308818,"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."}}