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Record W2111319547 · doi:10.1002/pen.20632

Measurement and prediction of thermal conductivity for hemp fiber reinforced composites

2007· article· en· W2111319547 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

VenuePolymer Engineering and Science · 2007
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMaterials scienceComposite materialThermal conductivityHeat fluxThermalFiberThermal conductivity measurementTransverse planeDrop (telecommunication)Heat transferStructural engineeringThermodynamicsMechanical engineering

Abstract

fetched live from OpenAlex

Abstract The thermal conductivity of hemp fiber reinforced polymer composites were studied from the steady state temperature drop across samples exposed to a known heat flux. The transverse and in‐plane thermal conductivities for oriented and randomly oriented composites for different volume fractions of fiber were investigated. Experimental results showed that the orientation of fibers has a significant effect on the thermal conductivity of composites. To validate the experimental results, the heating tests for the thermal conductivity measurements were simulated by a finite element model using the thermal conductivity values obtained from the experiments. Predicted temperatures show close agreement with measured temperatures. Moreover, the experimental results of thermal conductivities of composites at different directions were compared with two theoretical models and illustrated good agreement between the obtained results and models. POLYM. ENG. SCI. 47:977–983, 2007. © 2007 Society of Plastics Engineers

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 score0.016
Threshold uncertainty score0.332

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.226
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