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Record W2976906606 · doi:10.21595/vp.2019.20981

Cell dynamics and natural frequencies: scaling and shape matters

2019· article· en· W2976906606 on OpenAlexaff
C. V. Chandrashekara, Ayman Ahmed Mubeen, Arun Barathwaj R, Amith Basavaraju, M C Srividyadhare Kateel

Bibliographic record

VenueVibroengineering PROCEDIA · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCellular Mechanics and Interactions
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsScalingNatural frequencyFinite element methodStatistical physicsNormal modeFrequency scalingMode (computer interface)Field (mathematics)MechanicsDynamics (music)PhysicsMathematicsComputer scienceStructural engineeringEngineeringGeometryAcousticsVibration

Abstract

fetched live from OpenAlex

Cell dynamics is one of the most investigated areas under the field of biomechanics. Scaling plays a crucial role in determining the dynamic characteristics of biological systems. In the present investigation, cuboidal and cylindrical models of different scales are analysed to depict the dependence of natural frequency on the scaling factors. Three approaches, namely lumped mass system, finite element model (FEM) and numerical approach using Ansys are used to determine the fundamental natural frequencies. Different scaling factors, namely nano, micro (original size), millimeter and meter are considered for the analysis. The results indicate that the natural frequency varies inversely with the size of the cell by the same factor. A simple mathematical relation is derived to support this claim. Results are illustrated with numerical examples and corresponding mode shapes are reported.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.623
Threshold uncertainty score0.438

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 studies0.0000.000
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 head0.002
GPT teacher head0.174
Teacher spread0.172 · 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

Citations1
Published2019
Admission routes1
Has abstractyes

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