{"id":"W2899816098","doi":"10.1109/jmems.2018.2877736","title":"In-Plane High-Sensitivity Capacitive Accelerometer in a 3-D CMOS-Compatible Surface Micromachining Process","year":2018,"lang":"en","type":"article","venue":"Journal of Microelectromechanical Systems","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University; École de Technologie Supérieure","funders":"King Abdulaziz City for Science and Technology; École de technologie supérieure; McGill University","keywords":"Accelerometer; Surface micromachining; Sensitivity (control systems); Microelectromechanical systems; Materials science; Capacitive sensing; Bulk micromachining; Proof mass; Optoelectronics; Photolithography; Electronic engineering; Computer science; Electrical engineering; Engineering; Fabrication","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":[0.000699705,0.0002454804,0.0007229532,0.0003469138,0.00003810779,0.00004347147,0.0002410419,0.0002138439,0.00001300534],"category_scores_gemma":[0.00008564412,0.0002164077,0.00007287291,0.0006102119,0.00005422712,0.0003722266,0.00003208095,0.0008433646,0.00001375097],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003268276,"about_ca_system_score_gemma":0.00003795695,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001515229,"about_ca_topic_score_gemma":0.0002604605,"domain_scores_codex":[0.9981927,0.0000570424,0.0007705321,0.0002065357,0.0002209271,0.0005522654],"domain_scores_gemma":[0.9992322,0.000154162,0.0002350854,0.000162434,0.0001361332,0.00007994648],"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":[0.00006419805,0.0000567524,0.00009456405,0.00008552207,0.00003994421,0.0001894986,0.0002278178,0.000822348,0.9978382,0.00009713136,0.0001427475,0.0003413045],"study_design_scores_gemma":[0.001141675,0.0007604544,0.0005476929,0.0004981966,0.00001558308,0.001008071,0.0003318048,0.001754089,0.9923158,0.001036703,0.0002654626,0.0003244505],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.99511,0.0006020609,0.003227875,0.00006450334,0.0006367333,0.0002049893,0.000008224832,0.00007965339,0.00006590083],"genre_scores_gemma":[0.9983043,0.0001102323,0.001301026,0.00002263305,0.0002005809,0.000004558359,0.000001108782,0.00003910394,0.00001645439],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005522355,"threshold_uncertainty_score":0.882485,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0093119067362781,"score_gpt":0.2414307019171802,"score_spread":0.2321187951809021,"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."}}