{"id":"W2519897456","doi":"10.1049/el.2016.3123","title":"Ambient electromagnetic energy harvesting system for on‐body sensors","year":2016,"lang":"en","type":"article","venue":"Electronics Letters","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":12,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Energy harvesting; Electrical engineering; Energy (signal processing); Acoustics; Computer science; Electronic engineering; Physics; Engineering","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.000204906,0.0003594045,0.0002886588,0.0001432985,0.0001332776,0.00006119897,0.0003013287,0.000126681,0.000007324114],"category_scores_gemma":[0.00005797686,0.0003053411,0.0001315024,0.0002178096,0.00004763592,0.0001071243,0.00002118324,0.0002116297,0.00002547519],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007834777,"about_ca_system_score_gemma":0.00003181932,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001045696,"about_ca_topic_score_gemma":0.00002502037,"domain_scores_codex":[0.9977117,0.00006049205,0.0003604905,0.0004217245,0.0002447647,0.001200855],"domain_scores_gemma":[0.9988439,0.0004734361,0.00007708684,0.000432442,0.00003955909,0.0001335747],"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":[0.00002226014,0.00001644406,0.00002907407,0.00008188112,0.0001070774,0.00001692777,0.00001908171,0.1148461,0.8406193,0.02894625,0.007002818,0.008292795],"study_design_scores_gemma":[0.002295001,0.0009896893,0.000160111,0.0008808679,0.0001078383,0.0001189621,0.00001274977,0.1648728,0.705496,0.0002385334,0.1231427,0.001684701],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.859341,0.0007631714,0.1326668,0.001338837,0.001147327,0.0003139693,0.00001250646,0.002407981,0.002008406],"genre_scores_gemma":[0.9964594,0.00007247928,0.001412025,0.0004445094,0.0005714468,0.0001805183,0.00001182394,0.0001820256,0.0006657536],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1371185,"threshold_uncertainty_score":0.9999399,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004803326768943,"score_gpt":0.1762035724825604,"score_spread":0.1714002457136174,"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."}}