{"id":"W4416129079","doi":"10.1038/s41378-025-01065-4","title":"Machine learning-driven metastructure design for sensor-free linearization of MEMS electrothermal actuators","year":2025,"lang":"en","type":"article","venue":"Microsystems & Nanoengineering","topic":"Aeroelasticity and Vibration Control","field":"Engineering","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; McGill University","funders":"Natural Sciences and Engineering Research Council of Canada; Government of Canada; Hitachi America","keywords":"Actuator; Microelectromechanical systems; Nonlinear system; Linearization; Finite element method; Displacement (psychology); Stiffness; Voltage","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002366585,0.0003716502,0.0002985371,0.0001732614,0.0001519807,0.0002855076,0.0005456913,0.0003474226,0.0009291693],"category_scores_gemma":[0.0004283493,0.0002734019,0.0002638942,0.000135583,0.0003218382,0.0004463837,0.0003366243,0.0003702353,0.0002285679],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004332412,"about_ca_system_score_gemma":0.0004552625,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005848375,"about_ca_topic_score_gemma":0.001538611,"domain_scores_codex":[0.9998678,0.00001772755,0.000007169762,0.000031224,0.00006284353,0.00001323167],"domain_scores_gemma":[0.9998769,0.00004338905,0.00003337497,0.00001458857,0.00002568973,0.00000604821],"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":[0.00007909418,0.00006163004,0.0004055928,0.0001907629,0.00003214768,0.00009901284,0.00007518089,0.7580692,0.1750928,0.008916967,0.0005707797,0.05640688],"study_design_scores_gemma":[0.000004296465,0.00005359853,0.0000899974,0.000004369258,0.000003173881,0.00001476782,0.000003735518,0.9852023,0.0131753,0.0007312151,0.0007123418,0.000004903704],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.03917061,0.000201664,0.9574587,0.0001011741,0.00001890574,0.00004182855,0.00003550413,0.0003910346,0.002580479],"genre_scores_gemma":[0.8416485,0.0001149842,0.1562255,0.00006043722,0.0000111666,0.0001301293,0.00006989218,0.00005376726,0.001685657],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0009291693,"threshold_uncertainty_score":0.00314337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005634966538122666,"score_gpt":0.1930166483370062,"score_spread":0.1873816817988835,"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."}}