{"id":"W2999172043","doi":"10.1109/sensors43011.2019.8956939","title":"Design and Characterization of a Tuning Fork Microresonator Based on Nonlinear 2:1 Internal Resonance","year":2019,"lang":"en","type":"article","venue":"","topic":"Advanced MEMS and NEMS Technologies","field":"Engineering","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Simon Fraser University","funders":"","keywords":"Tuning fork; Resonator; Resonance (particle physics); Microelectromechanical systems; Nonlinear system; Surface micromachining; Mechanical resonance; Natural frequency; Excitation; Gyroscope; Physics; Optoelectronics; Materials science; Acoustics; Optics; Vibration; Atomic physics; Fabrication","routes":{"ca_aff":true,"ca_fund":false,"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":[0.0004206097,0.0003358462,0.0003783923,0.000252364,0.0002427834,0.0002848295,0.0004361263,0.0006313088,0.0004244555],"category_scores_gemma":[0.0004442622,0.0002365565,0.0001838785,0.0001197922,0.0003298844,0.0003553436,0.0002032788,0.0002288082,0.0002486683],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003403302,"about_ca_system_score_gemma":0.0003382417,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005216997,"about_ca_topic_score_gemma":0.0009271813,"domain_scores_codex":[0.9996506,0.00002474039,0.00001957636,0.0001079374,0.0001567438,0.00004045467],"domain_scores_gemma":[0.9997172,0.0000638674,0.00008075312,0.00003623184,0.00006749584,0.0000343999],"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":[0.000008997787,0.000005704465,0.0001541436,0.00002337557,0.00000174101,0.00001974217,0.00002212055,0.0001060502,0.9988033,0.00005766434,0.0000184862,0.000778544],"study_design_scores_gemma":[0.000008859926,0.0002561452,0.002376191,0.000003045681,0.000007577024,0.000123857,0.00001797506,0.00550198,0.9899986,0.00001583265,0.001677306,0.00001264354],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9634621,0.0006125903,0.03341827,0.0001433163,0.00005371348,0.0001870638,0.0002164381,0.0002274972,0.001679023],"genre_scores_gemma":[0.9421759,0.0002141844,0.05560578,0.00003683984,0.00001828084,0.0001211479,0.0001464423,0.00002572353,0.001655607],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0006313088,"threshold_uncertainty_score":0.002469242,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007366181290597868,"score_gpt":0.2001272591753638,"score_spread":0.1927610778847659,"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."}}