{"id":"W3036291007","doi":"10.1016/j.isci.2020.101286","title":"Triboelectric Nanogenerator versus Piezoelectric Generator at Low Frequency (&lt;4 Hz): A Quantitative Comparison","year":2020,"lang":"en","type":"article","venue":"iScience","topic":"Advanced Sensor and Energy Harvesting Materials","field":"Engineering","cited_by":129,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University; University of Toronto","funders":"","keywords":"Triboelectric effect; Energy harvesting; Nanogenerator; Rectifier (neural networks); Electrical engineering; Capacitor; Generator (circuit theory); Piezoelectricity; Power (physics); Low frequency; Physics; Acoustics; Materials science; Optoelectronics; Computer science; Voltage; Engineering; 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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0001099977,0.0002577333,0.000329395,0.00009648355,0.0002303747,0.00008583826,0.0003488666,0.00007614121,0.0001021629],"category_scores_gemma":[0.0003339842,0.0002480327,0.0000604487,0.001335005,0.00008535011,0.0002705292,0.0000464273,0.0001303907,0.000262057],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001727391,"about_ca_system_score_gemma":0.00005542582,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0000110005,"about_ca_topic_score_gemma":0.00002162884,"domain_scores_codex":[0.998313,0.00005270511,0.0003506373,0.0004257063,0.0003029583,0.000555047],"domain_scores_gemma":[0.9992759,0.0001173894,0.00007359005,0.0002025552,0.00006640628,0.000264164],"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":[0.00004519938,0.00001281223,0.00007846828,0.00002522701,0.00001291781,0.00001399472,0.0003681557,0.07009473,0.9252377,0.0008826859,0.001385912,0.001842161],"study_design_scores_gemma":[0.0007540003,0.0004229734,0.0001219394,0.00001686176,0.0000164699,0.000005837132,0.00002982509,0.2269204,0.7686889,0.00006308519,0.002461192,0.0004985292],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9651511,0.002316034,0.02958714,0.00008442173,0.0008343491,0.0001404868,0.00002419767,0.0005623592,0.001299909],"genre_scores_gemma":[0.99103,0.00007736034,0.008397299,0.0001449704,0.0002129531,0.00002341697,0.00001131062,0.00004009246,0.00006262979],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1568256,"threshold_uncertainty_score":0.9999972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03852733294761523,"score_gpt":0.264462959638478,"score_spread":0.2259356266908628,"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."}}