{"id":"W2342627765","doi":"10.1177/1045389x16642536","title":"Modeling and parametric study of a force-amplified compressive-mode piezoelectric energy harvester","year":2016,"lang":"en","type":"article","venue":"Journal of Intelligent Material Systems and Structures","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":30,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Energy harvesting; Nonlinear system; Piezoelectricity; Parametric statistics; Power (physics); Excitation; Bandwidth (computing); Energy (signal processing); Acoustics; Electrical engineering; Engineering; Physics; Telecommunications","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":[0.0002422534,0.0002914134,0.0003498102,0.0001904829,0.0003391795,0.0005223876,0.001004048,0.001073472,0.001916351],"category_scores_gemma":[0.0004892514,0.000313028,0.0003314682,0.000296971,0.0007572086,0.001123144,0.0004226179,0.0004109937,0.0004058277],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005193494,"about_ca_system_score_gemma":0.000548157,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001543932,"about_ca_topic_score_gemma":0.001250018,"domain_scores_codex":[0.9998863,0.00001504093,0.00000397438,0.0000316634,0.00004816512,0.00001491972],"domain_scores_gemma":[0.9998742,0.00005300586,0.00002848646,0.00001831634,0.00001896558,0.00000700811],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001037356,0.00009637238,0.001164975,0.0001496479,0.00002530848,0.000646117,0.0003720537,0.8016097,0.1669141,0.01673966,0.000604007,0.01157434],"study_design_scores_gemma":[0.000004712134,0.00003747632,0.0002072002,0.000004168167,0.000004859673,0.00005081815,0.00001796118,0.9928122,0.005394097,0.0007040974,0.0007529912,0.000009410801],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4439701,0.000780688,0.5046762,0.001201475,0.00005819853,0.0002357281,0.0004119869,0.0006612788,0.04800436],"genre_scores_gemma":[0.972047,0.0003352927,0.01948606,0.00004032733,0.00001081708,0.0001119325,0.0000448691,0.00003248294,0.007891264],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001916351,"threshold_uncertainty_score":0.006410837,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0188109096962944,"score_gpt":0.241141801783338,"score_spread":0.2223308920870436,"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."}}