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Record W1955950364 · doi:10.1115/imece2014-39676

A Multiscale Model to Determine the Stiffness of Collenchyma Tissue in Rheum Rhabarbarum

2014· article· en· W1955950364 on OpenAlexafffund
Tanvir R. Faisal, Nicolay Hristozov, Tamara L. Western, Alejandro D. Rey, Damiano Pasini

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicTree Root and Stability Studies
Canadian institutionsMcGill University
FundersFonds de recherche du Québec – Nature et technologiesMcGill University
KeywordsStiffnessMicrofibrilStiffeningMaterials scienceFinite element methodComposite materialBiomedical engineeringStructural engineeringChemistryCelluloseEngineering

Abstract

fetched live from OpenAlex

The stiffness of plant tissue largely influences the overall mechanical response of plant organs, such as stems, branches and leaf petioles. This work examines the structural hierarchy of the plant tissue; in particular of the collenchyma tissue of the Rheum rhabarbarum. The goal of the paper is to develop a multiscale model capturing features of two orders of its structural hierarchy: cell wall and tissue architecture. The former is considered as a fiber reinforced composite, where the cellulose microfibril (CMF) is the main load bearing component. The longitudinal stiffness of the middle (S2) layer of the secondary cell wall is affected by the microfibril angle (MFA) up to 45° to a greater extent, which in turn plays a role in the overall wall stiffness. The latter, i.e. tissue architecture, influences the tissue stiffness through its random distribution of cells. Finite-edge Centroidal Voronoi Tessellation (FECVT) is used to model the non-periodic microstructure of the rhubarb collenchyma, whose effective elastic properties are obtained through finite element analysis. The results from the FECVT model show that the effective stiffness in the longitudinal direction is 15 to 25% higher than that in the transverse direction for relative density between 5 and 30%. The variation reflects the stiffening effect of the shape and size of the cells in the collenchyma tissue, as well as its aperiodic cellular distribution.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.185
Threshold uncertainty score0.999

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 head0.017
GPT teacher head0.230
Teacher spread0.213 · 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 designSimulation or modeling
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

Citations0
Published2014
Admission routes2
Has abstractyes

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