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Record W4405122154 · doi:10.4028/p-pse0ws

Effects of Temperature and Pressing Time on Flexural Properties of Binderless Chipboards from Coconut Chip

2024· article· en· W4405122154 on OpenAlex
H. Liem, Zunaida Zakaria, Le Quan Ngoc Tran

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueKey engineering materials · 2024
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsFlexural strengthMaterials sciencePressingComposite materialHuskYoung's modulusCompression moldingRaw materialHot pressingFlexural modulusMold

Abstract

fetched live from OpenAlex

Coconut husk materials have become emerging candidates for the industry of furniture and housing due to their properties and abundance in tropical regions. This study explores using coconut chips, a sustainable and biodegradable resource as an alternative material to produce eco-friendly fibrous boards. The binderless chipboards were fabricated from coconut chips using compression molding at different pressing temperatures and times. The binderless chipboards’ thickness, density, and flexural properties were investigated. Results indicate that higher pressing temperatures and longer pressing times result in reduced thickness, lower density, and improved modulus of rupture (MOR) and modulus of elasticity (MOE). Based on the findings of this study, it is suggested that binderless chipboards produced under optimized conditions could offer a viable alternative to traditional wood based particleboards.

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.

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 score0.003
Threshold uncertainty score0.667

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 head0.005
GPT teacher head0.191
Teacher spread0.186 · 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