{"id":"W2070251644","doi":"10.5539/mas.v3n9p16","title":"Optimal Design of Capacitive Micro Cantilever Beam Accelerometer","year":2009,"lang":"en","type":"article","venue":"Modern Applied Science","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Universiti Sains Malaysia","keywords":"Cantilever; Accelerometer; Finite element method; Capacitive sensing; Proof mass; Deflection (physics); Beam (structure); Capacitance; Acceleration; Optimal design; Materials science; Acoustics; Computer science; Structural engineering; Electrode; Physics; Engineering; Optics; Composite material; Classical mechanics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003494693,0.0007209792,0.0005853287,0.0004206863,0.0002782675,0.0005698497,0.0005271964,0.0008537825,0.001234043],"category_scores_gemma":[0.001031827,0.0005175689,0.000298815,0.0002363421,0.000319347,0.0004329244,0.0003397415,0.0002430729,0.0003126117],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005291152,"about_ca_system_score_gemma":0.0006976494,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009978676,"about_ca_topic_score_gemma":0.001527901,"domain_scores_codex":[0.9995093,0.00007011906,0.00002459791,0.0001205023,0.0002170826,0.00005835414],"domain_scores_gemma":[0.9996877,0.00008180927,0.00007339037,0.00001686008,0.0001211855,0.00001911693],"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":[0.0004115447,0.000158971,0.002606422,0.0008031683,0.00009181752,0.0003877369,0.0001628325,0.4927925,0.3712397,0.01065307,0.002317619,0.1183747],"study_design_scores_gemma":[0.00009458835,0.000512885,0.001780027,0.00004262781,0.00006225409,0.0002418681,0.00009111762,0.9481524,0.04128867,0.00258055,0.005108689,0.00004443163],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1888345,0.002280186,0.7870504,0.0005410374,0.0001644991,0.0002416852,0.0001728918,0.0004218151,0.02029296],"genre_scores_gemma":[0.8327568,0.0005465684,0.16449,0.00008582706,0.00003106323,0.000185734,0.00006257029,0.0000269995,0.001814538],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.001234043,"threshold_uncertainty_score":0.004128337,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01993473878148429,"score_gpt":0.225092362531815,"score_spread":0.2051576237503307,"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."}}