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Record W4320026224 · doi:10.23960/jsl.v11i1.614

Physical and Mechanical Properties of Oriented Flattened Bamboo Boards from Ater (Gigantochloa atter) and Betung (Dendrocalamus asper) Bamboos

2022· article· en· W4320026224 on OpenAlexaboutno aff
Alfira Ramadhani Putri, Nur Alam, Ulfa Adzkia, Yusup Amin, I Wayan Darmawan, Lina Karlinasari

Bibliographic record

VenueJurnal Sylva Lestari · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBamboo properties and applications
Canadian institutionsnot available
Fundersnot available
KeywordsBambooComposite materialFlexural strengthMaterials scienceAbsorption of water

Abstract

fetched live from OpenAlex

Bamboo-based composite has been used widely for building components and furniture. Oriented flattened bamboo board (OFBB) is a composite board consisting of oriented structure sheets of flattening bamboo. This study aimed to analyze the physical and mechanical properties of the OFBB from ater (Gigantochloa atter) and betung (Dendrocalamus asper) bamboo. A three-layer flattened bamboo board using the isocyanate resin with a density target of 0.6 g/cm3 was applied. The characteristics of raw bamboo, the contact angle of OFBB, and board properties of density, moisture content, thickness swelling, and water absorption, as well as bending, internal bonding (IB), and compressive strength properties were determined to evaluate the quality of the OFBB. Based on the findings, the thin wall thickness of ater bamboo enhanced the physical and mechanical properties of the OFBB compared to the higher wall thickness of betung bamboo. Therefore, further development in bamboo composite products with those anatomical properties seems promising. The dimensional stability and bending properties of OFBB from ater bamboo met the quality of first grade of the Canadian Standard for OSB and waferboard, except for the IB strength. Keywords: Bamboo wall thickness, contact angle, Dendrocalamus asper, Gigantochloa atter, oriented flattened bamboo board

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 score0.662
Threshold uncertainty score0.379

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 head0.192
Teacher spread0.176 · 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

Citations3
Published2022
Admission routes1
Has abstractyes

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