{"id":"W2143663321","doi":"10.1109/ats.2010.32","title":"Built-In Self-Test for Capacitive MEMS Using a Charge Control Technique","year":2010,"lang":"en","type":"article","venue":"","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"CMC Microsystems","keywords":"Capacitive sensing; Microelectromechanical systems; Capacitance; Built-in self-test; Device under test; Electronic engineering; Calibration; Digital control; Charge control; Time domain; Engineering; Materials science; Electrical engineering; Computer science; Optoelectronics; Physics; Scattering parameters; Power (physics)","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":[0.0003007898,0.0003017592,0.0001979077,0.0004491461,0.0001980805,0.0003358827,0.0007912766,0.0003174912,0.001269442],"category_scores_gemma":[0.001000578,0.0001503126,0.0001678164,0.0002074346,0.0003943043,0.0006198747,0.000452577,0.0003956525,0.0001899799],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000303352,"about_ca_system_score_gemma":0.0002695326,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000238657,"about_ca_topic_score_gemma":0.0005204552,"domain_scores_codex":[0.9995901,0.00004824407,0.00001506351,0.00004972085,0.0002702089,0.00002662967],"domain_scores_gemma":[0.9992023,0.0002207805,0.0001460694,0.0001540772,0.0002267878,0.00005001071],"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":[0.0001816929,0.00009374406,0.0018133,0.0001144217,0.00002169237,0.0002233658,0.00009091343,0.001456714,0.925186,0.002758882,0.0007151117,0.06734423],"study_design_scores_gemma":[0.00003518386,0.0006457851,0.002407423,0.000008053071,0.0000192259,0.0008667918,0.00001606014,0.03007943,0.9621758,0.0003965848,0.003322881,0.00002665698],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.4457904,0.001088404,0.544362,0.0003196117,0.0003002944,0.0002565492,0.0001712802,0.003140251,0.004571312],"genre_scores_gemma":[0.9275309,0.0001303029,0.07005297,0.0001502606,0.00005440247,0.00007195125,0.00008062954,0.00007213029,0.001856435],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001269442,"threshold_uncertainty_score":0.004246652,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009408956877610309,"score_gpt":0.2420596732659258,"score_spread":0.2326507163883154,"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."}}