{"id":"W1988004924","doi":"10.1115/detc2013-13340","title":"Micro Cantilever Electrostatic Energy Harvester","year":2013,"lang":"en","type":"article","venue":"","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Waterloo","funders":"","keywords":"Cantilever; Electret; Deflection (physics); Vibration; Voltage; Materials science; Nonlinear system; Mechanics; Electrostatics; Electric potential energy; Beam (structure); Energy harvesting; Excitation; Mechanical energy; Triboelectric effect; Acoustics; Structural engineering; Physics; Energy (signal processing); Classical mechanics; Engineering; Electrical engineering; Power (physics); Composite material","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":[0.00007772199,0.0002091416,0.0003403523,0.0001136828,0.0001978536,0.0002757157,0.0006960068,0.0007805649,0.002197645],"category_scores_gemma":[0.0001218508,0.0001165002,0.0002544597,0.0001072283,0.0002839429,0.000520893,0.0002908014,0.0002573245,0.0003235731],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002010017,"about_ca_system_score_gemma":0.0001981717,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008006697,"about_ca_topic_score_gemma":0.0005774271,"domain_scores_codex":[0.9999386,0.000005266017,0.000002105544,0.00001815873,0.00002818213,0.000007646024],"domain_scores_gemma":[0.9999683,0.000009716246,0.000004618742,0.000005846024,0.000008362518,0.000003162802],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001279386,0.0001225062,0.001497143,0.0002226277,0.00005085154,0.0008014633,0.0001909589,0.5872815,0.3329967,0.04751421,0.001669814,0.02752418],"study_design_scores_gemma":[0.00001644707,0.00007697668,0.000655733,0.000006786619,0.000008100124,0.0001631685,0.00001873379,0.9846147,0.007730562,0.003006525,0.003691855,0.00001039085],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.313589,0.001223437,0.644953,0.0007376622,0.0001567755,0.0001135851,0.0004560854,0.000441174,0.0383294],"genre_scores_gemma":[0.9296388,0.0006610202,0.04403558,0.0001512703,0.00003307889,0.0001600934,0.0001356818,0.00002780794,0.0251567],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.002197645,"threshold_uncertainty_score":0.007351875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004970166128573377,"score_gpt":0.1650005893958861,"score_spread":0.1600304232673127,"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."}}