MétaCan
Menu
Back to cohort
Record W2012387969 · doi:10.1002/mame.200300276

Structure Property Correlation of Thermally Treated Hemp Fiber

2004· article· en· W2012387969 on OpenAlexaff
Bhuwan M. Prasad, Mohini Sain, D. N. Roy

Bibliographic record

VenueMacromolecular Materials and Engineering · 2004
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceMicrographComposite materialBast fibreFiberScanning electron microscopeOptical microscopeInert gasRaw materialInertComposite numberCellulose fiberChemistry

Abstract

fetched live from OpenAlex

Abstract Summary: Hemp ( Cannabis sativa L. ) is an important ligno‐cellulosic raw material for the manufacture of cost‐effective environmentally friendly composite materials. Hemp plant samples of different initial condition (stem and bast fibers) were subjected to heating varying the temperature (from 160 to 260 °C) and the ambient heating environment (air and inert atmosphere). Weight measurements showed that all heat treatment resulted in a reduced weight of hemp. Those treated in air showed drastic decline in weight compared with those treated under nitrogen, especially at a temperature higher than 220 °C. Observation using optical and scanning microscope showed the possibilities of opening up of the fiber bundles in both heating environments. However, higher temperature and presence of air had a more severe effect on fibers and associated tissues compared to effects under nitrogen. Heat treatment at 220 °C under nitrogen seemed to provide enough fiber opening without affecting tissues of the fibers. SEM micrograph of the cross‐section of hemp fiber heat treated in air environment. magnified image SEM micrograph of the cross‐section of hemp fiber heat treated in air environment.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.016
Threshold uncertainty score0.432

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 head0.004
GPT teacher head0.178
Teacher spread0.175 · 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

Citations16
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueMacromolecular Materials and EngineeringSame topicNatural Fiber Reinforced CompositesFrench-language works237,207