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Record W2983757943 · doi:10.18280/rcma.290502

Quality of the Multi-scale Interphase of Hemp Stems: Retting Effect

2019· article· fr· W2983757943 on OpenAlexvenueno aff
Samuel Réquilé, Antoine Le Duigou, Alain Bourmaud, Christophe Baley

Bibliographic record

VenueRevue des composites et des matériaux avancés · 2019
Typearticle
Languagefr
FieldEngineering
TopicCatalysis and Hydrodesulfurization Studies
Canadian institutionsnot available
Fundersnot available
KeywordsRettingQuality (philosophy)Scale (ratio)Agricultural engineeringPulp and paper industryEngineeringPhysicsGeographyCartography

Abstract

fetched live from OpenAlex

The control of hemp plant harvesting, in particular the retting process, represents the major step for the development of high-performance hemp biocomposites. In this study, the consequences of hemp retting on the ease of fibre extraction and tensile properties of elementary hemp fibres is explored. Stem peeling experiments are combined with scanning electron microscopy (SEM) to investigate the influence of the retting degree in plants. After studying the evolution of fracture energy at the fibre/woody core interphase within the stem, this work investigates interphase fracture mechanisms during peeling experiments which aims to understand the evolution of fibre bundle cohesion during retting. A drastic drop of fracture energy reveals the impact of retting on the ease of peeling the outer tissue of the stem (containing fibre bundles). The positive impact of retting on various fibre defects combined together leads to a 33 % increase in the tangent modulus between non-retted and retted fibres, highlighting the importance of understanding the retting process to open up to new markets for biocomposites.

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)
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 score0.205
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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 head0.052
GPT teacher head0.310
Teacher spread0.258 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

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