{"id":"W2025628761","doi":"10.1109/aps.2013.6711183","title":"Harvesting electromagnetic energy using metamaterial particles","year":2013,"lang":"en","type":"article","venue":"","topic":"Metamaterials and Metasurfaces Applications","field":"Materials Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metamaterial; Electromagnetic radiation; Resonator; Split-ring resonator; Resistive touchscreen; Energy harvesting; Physics; Electromagnetic field; Energy (signal processing); Electromagnetic simulation; Resonance (particle physics); Electromagnetics; Range (aeronautics); Optoelectronics; Acoustics; Optics; Materials science; Electrical engineering; Electronic engineering; Engineering; Engineering physics","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":[0.0001012692,0.000130772,0.000203558,0.0001124834,0.0001327985,0.0002906069,0.0002583355,0.0002902782,0.0007816748],"category_scores_gemma":[0.0001210915,0.0001066382,0.0001682701,0.00007811766,0.0001911116,0.000383155,0.0002502416,0.0001826348,0.0003915605],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001170764,"about_ca_system_score_gemma":0.00006577708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003183882,"about_ca_topic_score_gemma":0.00005844004,"domain_scores_codex":[0.9999577,0.000006993165,0.000002313383,0.000009623594,0.00001660415,0.000006812211],"domain_scores_gemma":[0.9999527,0.00001674815,0.00001152744,0.000009211761,0.000005264384,0.000004537421],"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":[0.00005130094,0.00001930807,0.0001256357,0.00004546139,0.000007237349,0.00009055996,0.00002438381,0.002316409,0.9885736,0.003130845,0.0001327092,0.005482666],"study_design_scores_gemma":[0.000041112,0.0002607519,0.0004795638,0.00000880752,0.00001689051,0.0002113881,0.00003383217,0.04942013,0.9419568,0.001650621,0.005902636,0.00001759681],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9162215,0.0007917527,0.07495692,0.0003075763,0.00009881228,0.00002673332,0.00005519231,0.0003698533,0.007171584],"genre_scores_gemma":[0.9708961,0.0001952261,0.02634528,0.00004676214,0.00001156581,0.00001956404,0.00002797604,0.00002169148,0.002435807],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0007816748,"threshold_uncertainty_score":0.002614975,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02933906270778774,"score_gpt":0.2438589616609765,"score_spread":0.2145198989531887,"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."}}