{"id":"W2067128569","doi":"10.1117/12.2017814","title":"Design, fabrication and characterization of a micromachined piezoelectric energy harvester excited by ambient vibrations","year":2013,"lang":"en","type":"article","venue":"Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Cantilever; Fabrication; Piezoelectricity; Acceleration; Materials science; Vibration; Proof mass; Surface micromachining; Silicon; Energy harvesting; Beam (structure); Optoelectronics; Acoustics; Characterization (materials science); Power (physics); Microelectromechanical systems; Electrical engineering; Physics; Engineering; Optics; Nanotechnology; 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":[0.0002157226,0.0002444373,0.0003641932,0.0001589307,0.0001986254,0.0003736425,0.0007392203,0.000555616,0.0008239517],"category_scores_gemma":[0.0002856494,0.000261142,0.0002182962,0.0001566591,0.0003026027,0.0005523357,0.0002309251,0.0003638724,0.0003122584],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003266518,"about_ca_system_score_gemma":0.0004252951,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003512835,"about_ca_topic_score_gemma":0.0008797475,"domain_scores_codex":[0.9997413,0.00001170696,0.00001498644,0.0000807168,0.0001311322,0.0000201498],"domain_scores_gemma":[0.9997833,0.00004709342,0.00005851137,0.00003591145,0.00005917534,0.00001588984],"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":[0.00001965428,0.00001500931,0.0002164057,0.00008120208,0.000007121506,0.00006815531,0.00002947228,0.0008753532,0.9934394,0.0002016517,0.00009170626,0.004954848],"study_design_scores_gemma":[0.00002048912,0.0003336901,0.003289923,0.000008120049,0.0000195053,0.0004289927,0.00003315484,0.01030522,0.9804299,0.0001078944,0.00500187,0.00002122387],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.7449456,0.00178778,0.2454762,0.0004203825,0.0002249326,0.0004171011,0.000630388,0.001173067,0.004924571],"genre_scores_gemma":[0.7537596,0.0005917971,0.2389253,0.0001093313,0.00003584151,0.0002739779,0.0003146457,0.00005349973,0.005936],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0008239517,"threshold_uncertainty_score":0.002756357,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008669804469071432,"score_gpt":0.1946869917079055,"score_spread":0.186017187238834,"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."}}