{"id":"W3021029423","doi":"10.1088/1361-665x/ab9149","title":"Application of artificial intelligence and evolutionary algorithms in simulation-based optimal design of a piezoelectric energy harvester","year":2020,"lang":"en","type":"article","venue":"Smart Materials and Structures","topic":"Innovative Energy Harvesting Technologies","field":"Engineering","cited_by":29,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Manitoba","funders":"Research Manitoba","keywords":"Interfacing; Artificial neural network; Optimal design; Evolutionary algorithm; Computer science; Genetic algorithm; Energy harvesting; Electronic engineering; Engineering; Control theory (sociology); Algorithm; Energy (signal processing); Artificial intelligence; Mathematics; Machine learning","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00006572423,0.00009175582,0.0001664244,0.0001018828,0.00001616592,0.00001601985,0.00005858507,0.00007053543,0.000005170376],"category_scores_gemma":[0.00008306156,0.00008645023,0.000006893932,0.0002124668,0.00008006534,0.00007354601,0.00002068637,0.00003505623,7.256922e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008463112,"about_ca_system_score_gemma":0.00001111588,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003907148,"about_ca_topic_score_gemma":0.000001699687,"domain_scores_codex":[0.9994388,0.00002694769,0.0002698257,0.0001182906,0.00006038029,0.00008571488],"domain_scores_gemma":[0.9997293,0.00009413542,0.00005993564,0.0000649732,0.00003810265,0.00001355968],"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":[0.00004101696,0.000003846304,0.0003911288,0.00008175868,0.00000625332,5.331295e-7,0.00005609282,0.7986152,0.1739794,0.009779134,0.000002801906,0.01704275],"study_design_scores_gemma":[0.00004691418,0.00005693448,0.006093461,0.000009581699,0.000003491195,4.440649e-7,0.00001453971,0.6425576,0.3445936,0.006538653,0.00001024535,0.00007461519],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4315508,0.00009184517,0.5682092,0.00001698167,0.00002398778,0.00005382147,0.00001144905,0.00004010227,0.000001796426],"genre_scores_gemma":[0.965333,0.00001004141,0.03459022,0.00001248206,0.0000234187,0.00001152836,0.00000955074,0.000009359353,3.928646e-7],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.5337822,"threshold_uncertainty_score":0.3525338,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02463424837735416,"score_gpt":0.2335842630718002,"score_spread":0.208950014694446,"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."}}