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Record W7047931626

Hybrid Sandwich Particleboard Made with Sugarcane, PÃnus Taeda Thermally Treated and Malva Fibre from Amazon

2017· article· en· W7047931626 on OpenAlexaboutno aff

Bibliographic record

VenueThe Scientific Electronic Library Online (Fundação de Amparo à Pesquisa do Estado de São Paulo) · 2017
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsFlexural strengthPinus <genus>BagasseComposite numberCompactionYoung's modulusSwelling
DOInot available

Abstract

fetched live from OpenAlex

A multilayer particleboard panels, consisted of sugarcane bagasse reinforced composite as core material and hybrid composites made with Pinus taeda particles and Malva fibres as facing materials, were designed and evaluated in this work. Tukey test was used to identify the effect of the facing material, considering different combinations of Pinus taeda particles and Malva fibres, on the bulk density, thickness swelling, flexural strength, flexural stiffness and X-ray densitometry. A spray-up process was used to spread castor oil based polyurethane resin upon the dispersive phases followed by a hot compaction at 100oC. The particleboards were classified as medium density panels in accordance to the Brazilian, American and Canadian Standards. All treatments reached the minimum strength except for elastic modulus. Tukey test demonstrated the flexural strength and modulus responses for all treatments were statistically similar. Hybrid particleboard consisted of 75% of Pinus taeda wood and 25% of Malva fibres revealed a promising sustainable material for furniture industries, combining strength, low-cost and lower thickness swelling values.

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), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0030.000
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0420.000

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 head0.011
GPT teacher head0.245
Teacher spread0.234 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

Explore more

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