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Record W2249260818 · doi:10.5539/mas.v10n1p133

Criteria of Equality of Modal Frequency of Micromechanical Gyroscopes-Accelerometers Sensitive Elements

2015· article· en· W2249260818 on OpenAlexvenueno aff
Б. Г. Коноплев, Igor Lysenko, O A Ezhova

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsModalVibrationCoincidenceSensitivity (control systems)Sense (electronics)GyroscopeAccelerometerPhysicsNormal modeModal analysisMode (computer interface)Span (engineering)AcousticsModal testingMaterials scienceStructural engineeringComputer scienceEngineeringElectronic engineeringElectrical engineeringQuantum mechanics

Abstract

fetched live from OpenAlex

<p class="zhengwen"><span lang="EN-GB">In this work the topology of the integrated micromechanical sensor of LL-type is developed. Using the condition of equality of modal frequencies of sensitive elements of the micromechanical sensor in both modes along the one axis the criterion of the coincidence is obtained, the criterion of modal frequencies of sensitive elements of the micromechanical sensor in a sense mode along the two axis is obtained, dependences of the ratio of beam length on thickness of a structural layer are showed, the results of numerical simulation of modal frequencies of the micromechanical sensor sensitive element in a drive mode or a sense mode is obtained using the criterion. Using the criterion, it is possible to achieve coincidence of intrinsic vibration frequencies of a sensitive element in a sense mode that provides the same sensitivity to the angular velocities. Coincidence of frequency of forced vibrations in a drive mode with vibration frequencies of a sense mode along both axis of sensitivity can be achieved by using electrostatic elasticity.</span></p>

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.045
GPT teacher head0.294
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2015
Admission routes1
Has abstractyes

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