{"id":"W3106702740","doi":"10.1109/ccece47787.2020.9255802","title":"An Energy Harvesting Solution for IoT Devices in 5G Networks","year":2020,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"","keywords":"Energy harvesting; Computer science; Rectifier (neural networks); Wireless; Schottky diode; Antenna (radio); Extremely high frequency; Internet of Things; Electrical engineering; Rectenna; Wireless sensor network; Energy (signal processing); Power (physics); Electronic engineering; Telecommunications; Embedded system; Diode; Computer network; Engineering; Physics","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":[0.00007371622,0.0001450479,0.0001147317,0.00008820303,0.0001567737,0.0002954522,0.0003017842,0.0003820937,0.001722794],"category_scores_gemma":[0.00008960498,0.00007059927,0.0001939317,0.0001596083,0.0001000496,0.0003941756,0.0001225691,0.0001793104,0.000577405],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001841178,"about_ca_system_score_gemma":0.0001182938,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001276426,"about_ca_topic_score_gemma":0.0003422701,"domain_scores_codex":[0.9999439,0.000009052966,0.000002294246,0.000009074316,0.00002857508,0.000007161021],"domain_scores_gemma":[0.9999777,0.000004324208,0.000004219697,0.000003005976,0.000009208196,0.00000160158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001225255,0.00008564828,0.000994446,0.0003796725,0.00005880353,0.000484897,0.0001750676,0.02601885,0.7725085,0.04323443,0.009348368,0.1465888],"study_design_scores_gemma":[0.00005100422,0.001076299,0.002348402,0.0001251954,0.0001182195,0.001554279,0.0002344799,0.3841603,0.4337665,0.01410478,0.1624008,0.0000597375],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2184867,0.003803635,0.7026157,0.002576435,0.0005898715,0.0001613254,0.000224116,0.001402467,0.07013965],"genre_scores_gemma":[0.9142433,0.001141011,0.06774208,0.0003641489,0.00004380212,0.00004383408,0.00008492411,0.00003168514,0.01630526],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001722794,"threshold_uncertainty_score":0.005763292,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01890761961682444,"score_gpt":0.2188868325154295,"score_spread":0.1999792128986051,"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."}}