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Record W2134504088 · doi:10.1002/app.40371

High performance of bamboo‐based fiber composites from long bamboo fiber bundles and phenolic resins

2014· article· en· W2134504088 on OpenAlex

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

VenueJournal of Applied Polymer Science · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversité du Québec à Chicoutimi
FundersChinese Academy of Forestry
KeywordsBambooMaterials scienceComposite materialFiberAbsorption of waterUltimate tensile strengthRaw materialChemistry

Abstract

fetched live from OpenAlex

ABSTRACT Lignocellulosic materials can be used for the development of bio‐based composites. This study explores the potential of long bamboo fiber bundles extracted directly from bamboo stems using the novel mechanical method and bamboo‐based fiber composites (BFC) fabricated using long bamboo fiber bundles and phenolic resins via cold pressing and thermal cure process. The microstructure, mechanical properties, and durability of BFC were evaluated, results being compared with raw bamboo and other commercialized bamboo fiber composites. The mechanical properties of BFC reinforced with 87% (w/w) long bamboo fiber bundles increased more than 50% than those of raw bamboo and were significantly higher than those of other bamboo‐based composites. Lower water absorption and thickness swelling were obtained in the case where bamboo fiber bundles with the small fineness. Higher tensile strength was obtained in the case where bamboo fiber bundles with large sizes of bamboo fiber bundles. © 2014 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2014 , 131 , 40371.

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)0.001
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 score0.013
Threshold uncertainty score0.811

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.007
GPT teacher head0.216
Teacher spread0.209 · 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