{"id":"W3114949270","doi":"10.3390/mi12010013","title":"Capacitive Based Micromachined Resonators for Low Level Mass Detection","year":2020,"lang":"en","type":"review","venue":"Micromachines","topic":"Mechanical and Optical Resonators","field":"Physics and Astronomy","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Windsor","funders":"Natural Sciences and Engineering Research Council of Canada; University of Windsor; CMC Microsystems","keywords":"Capacitive sensing; Surface micromachining; Resonator; Microfabrication; Sensitivity (control systems); Electronic engineering; Microelectromechanical systems; Finite element method; Engineering; Computer science; Materials science; Electrical engineering; Optoelectronics; Fabrication; Structural engineering","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":[0.0004337105,0.0006933623,0.000443803,0.000492386,0.0001776574,0.0006639652,0.0009060631,0.001003683,0.001687249],"category_scores_gemma":[0.0009131203,0.0003840408,0.0006262652,0.0004208776,0.0003528797,0.001129189,0.0003865103,0.0007473016,0.0008095707],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004919331,"about_ca_system_score_gemma":0.0002498525,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002286876,"about_ca_topic_score_gemma":0.0004593991,"domain_scores_codex":[0.9992369,0.0000791901,0.00003336513,0.0001971146,0.0004156462,0.00003779553],"domain_scores_gemma":[0.9996365,0.0001597207,0.00006554812,0.00002862753,0.0001010209,0.000008548788],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0000372538,0.00001786167,0.0002434109,0.001403429,0.00003467499,0.0001544641,0.00008108008,0.001975914,0.9318743,0.007218175,0.0008193856,0.05614005],"study_design_scores_gemma":[0.00001172411,0.0004367112,0.00110457,0.0001198672,0.00008080126,0.001056278,0.00007834873,0.01563006,0.9087747,0.002489988,0.07015036,0.00006660121],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.1021321,0.2069616,0.6554635,0.00154569,0.001761363,0.0002914915,0.0005165102,0.00144568,0.02988197],"genre_scores_gemma":[0.5188527,0.06705988,0.396705,0.0008312161,0.0006288301,0.0001653757,0.0003829694,0.0001264807,0.01524751],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.001687249,"threshold_uncertainty_score":0.005644441,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04144540255330829,"score_gpt":0.3084851801342331,"score_spread":0.2670397775809248,"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."}}