{"id":"W3006447537","doi":"10.1109/tcsi.2020.2971439","title":"An Ultra-Low-Power Low-Voltage WuTx With Built-In Analog Sensing for Self-Powered WSN","year":2020,"lang":"en","type":"article","venue":"IEEE Transactions on Circuits and Systems I Regular Papers","topic":"Energy Harvesting in Wireless Networks","field":"Engineering","cited_by":10,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Ultra low power; Low voltage; Electrical engineering; Power (physics); Low-power electronics; Voltage; Computer science; Engineering; Power consumption; 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":[0.0001518794,0.0001889208,0.0001997565,0.000177855,0.0001529083,0.0003489988,0.0006993385,0.0002603075,0.001014249],"category_scores_gemma":[0.000239773,0.0001606366,0.0001641416,0.0002077347,0.0001681014,0.0007622623,0.0004428171,0.0003357289,0.0003221999],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001439519,"about_ca_system_score_gemma":0.0001619309,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007580848,"about_ca_topic_score_gemma":0.0002271408,"domain_scores_codex":[0.9999123,0.00001207122,0.000006541814,0.00002122511,0.00003860655,0.000009308884],"domain_scores_gemma":[0.9999008,0.00002321456,0.00002476387,0.00001532546,0.00002582533,0.00001002098],"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":[0.00009846629,0.00005497025,0.001192582,0.0003166438,0.00002643057,0.0002191312,0.0001440331,0.001723992,0.897701,0.005058267,0.001162961,0.09230158],"study_design_scores_gemma":[0.00004387543,0.001402525,0.002899989,0.00007414758,0.00008610552,0.002459066,0.00009702336,0.05932999,0.891759,0.001478123,0.04032583,0.00004425039],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1837508,0.003230046,0.8010793,0.0004639251,0.0004191054,0.0001934361,0.0001110898,0.001563655,0.009188619],"genre_scores_gemma":[0.8335714,0.0009911897,0.1534189,0.0003260004,0.0001239713,0.0001047464,0.0001158389,0.00008906698,0.01125883],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001014249,"threshold_uncertainty_score":0.003393054,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01000927495682926,"score_gpt":0.1978688525428074,"score_spread":0.1878595775859782,"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."}}