Physical and Mechanical Properties of Oriented Flattened Bamboo Boards from Ater (Gigantochloa atter) and Betung (Dendrocalamus asper) Bamboos
Bibliographic record
Abstract
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
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".