{"id":"W2793823978","doi":"10.1002/adma.201705925","title":"Self‐Powered Wearable Electronics Based on Moisture Enabled Electricity Generation","year":2018,"lang":"en","type":"article","venue":"Advanced Materials","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":453,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"China Scholarship Council; Natural Sciences and Engineering Research Council of Canada; National Natural Science Foundation of China","keywords":"Electronics; Materials science; Moisture; Electricity; Wearable technology; Humidity; Wearable computer; Voltage; Electrical engineering; Generator (circuit theory); Nanotechnology; Computer science; Process engineering; Power (physics); Embedded system; Engineering; Composite material","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":[0.00008304541,0.0001910387,0.000143193,0.0001627632,0.00008289295,0.0002185404,0.0003386348,0.0002792588,0.001737339],"category_scores_gemma":[0.0001222618,0.0001142961,0.000148065,0.0001285575,0.0002250086,0.0005191552,0.0002752397,0.0001884953,0.0004700032],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001057718,"about_ca_system_score_gemma":0.0000558837,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004775163,"about_ca_topic_score_gemma":0.0000974739,"domain_scores_codex":[0.9999528,0.000004719819,0.000002814792,0.00001321317,0.00001840471,0.000008066611],"domain_scores_gemma":[0.9999464,0.00001427354,0.00001269048,0.000007286611,0.00001249442,0.00000691433],"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":[0.00002941654,0.00001851301,0.000161741,0.0000913044,0.000007441832,0.0001355428,0.00002347054,0.0003502914,0.9898486,0.00179753,0.0004346888,0.007101679],"study_design_scores_gemma":[0.00002101764,0.0002340348,0.001198285,0.0000115261,0.00001182997,0.0003391513,0.00002916731,0.01103362,0.9764765,0.001120169,0.009508491,0.00001613302],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8567278,0.002832086,0.1203152,0.0005349302,0.0005397043,0.0001268524,0.0003225012,0.0008250038,0.01777593],"genre_scores_gemma":[0.9767834,0.0007680299,0.0159173,0.0001257115,0.00005359246,0.00003828181,0.00007886188,0.00002954657,0.006205281],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001737339,"threshold_uncertainty_score":0.00581193,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008156527919434352,"score_gpt":0.2171659596751135,"score_spread":0.2090094317556792,"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."}}