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Record W1596404807 · doi:10.21829/myb.2014.203156

Comportamiento elástico de la madera de Acer rubrum y de Abies balsamea

2014· article· es· W1596404807 on OpenAlexaff
Saúl Antonio Hernández-Maldonado, Javier Ramón Sotomayor-Castellanos

Bibliographic record

VenueMadera y Bosques · 2014
Typearticle
Languagees
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsAbies balsameaPhysicsHumanitiesHorticultureArtBiologyBalsam

Abstract

fetched live from OpenAlex

El diseño de productos con alto valor agregado y el cálculo de estructuras en madera requieren de características elásticas confiables y relacionadas con un modelo teórico el cual explique de manera racional el comportamiento elástico de la madera. Se presentan la metodología y los resultados de la determinación experimental de las características elásticas de dos maderas canadienses: Acer rubrum y Abies balsamea. Las características examinadas fueron: módulos de elasticidad, módulos de rigidez y coeficientes de Poisson. Se realizaron experimentos de compresión, en el dominio elástico, de las direcciones de ortotropía de la madera: radial, tangencial y longitudinal. El contenido de humedad fue de 9% para A. rubrum y de 10% para A. balsamea. Las densidades de las maderas fueron de 651 kg/m3 y 393 kg/m3 respectivamente. A partir de las características obtenidas empíricamente, se analizaron las propiedades y las relaciones de ortotropía de la matriz de constantes elásticas del modelo elástico general. Los valores experimentales de las características elásticas de las maderas de A. rubrum y de A. balsamea, son comparables con valores correspondientes a estas maderas determinados en otros estudios. Igualmente, se demostró que los postulados de ortotropía del modelo elástico general son –con cierto nivel de confianza– válidos.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.006
GPT teacher head0.229
Teacher spread0.222 · 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.

Study designObservational
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

Citations3
Published2014
Admission routes1
Has abstractyes

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