{"id":"W2911942459","doi":"10.1109/mwscas.2018.8623832","title":"Efficient Dual-band Ultra-Low-Power RF Energy Harvesting Front-End for Wearable Devices","year":2018,"lang":"en","type":"article","venue":"","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":23,"is_retracted":false,"has_abstract":true,"ca_institutions":"Polytechnique Montréal","funders":"Natural Sciences and Engineering Research Council of Canada; CMC Microsystems","keywords":"Multi-band device; Electrical engineering; Energy harvesting; Radio frequency; Antenna (radio); Capacitor; CMOS; Capacitive sensing; Sensitivity (control systems); Voltage; Computer science; dBm; ISM band; Power (physics); Wearable computer; Electronic engineering; Engineering; Physics; Amplifier; Embedded system","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":[0.00009154601,0.0002637325,0.0002933183,0.000217459,0.0001421793,0.0003731286,0.0006765492,0.0004827862,0.001849477],"category_scores_gemma":[0.000146458,0.0001793006,0.00030961,0.0002063886,0.0001201957,0.0005772155,0.0002993676,0.0002859481,0.001294453],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001888457,"about_ca_system_score_gemma":0.0001023179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008118853,"about_ca_topic_score_gemma":0.0002672157,"domain_scores_codex":[0.9998983,0.000008496985,0.000005253446,0.00002669228,0.0000492691,0.0000119999],"domain_scores_gemma":[0.9999458,0.00001359146,0.000009282777,0.000006864354,0.0000200288,0.000004428918],"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":[0.0001087269,0.00006613721,0.0005354622,0.0002039823,0.00003016488,0.0002207288,0.0000569526,0.002776208,0.9144484,0.003462919,0.001983135,0.07610721],"study_design_scores_gemma":[0.0000324459,0.0004893728,0.002272935,0.00005680319,0.00006455912,0.00146314,0.00004084254,0.08884492,0.8710061,0.002099639,0.03358651,0.00004272497],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1488265,0.001757325,0.8330595,0.00045714,0.0002151618,0.0000704846,0.0001863383,0.001408985,0.01401861],"genre_scores_gemma":[0.7781105,0.00121055,0.1968814,0.0006848775,0.0001127407,0.00009561241,0.0002846421,0.0001201227,0.02249952],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001849477,"threshold_uncertainty_score":0.006187081,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008436112359497355,"score_gpt":0.207807540377743,"score_spread":0.1993714280182456,"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."}}