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Record W2085344568 · doi:10.1002/cjce.5450800517

Thermal Sensor to Monitor Mechanical Properties in Polymer/Fiber Composite Molding

2002· article· en· W2085344568 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2002
Typearticle
Languageen
FieldEngineering
TopicMechanical and Thermal Properties Analysis
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsMaterials scienceComposite materialThermal conductivityAxial symmetryComposite numberFiberHeat fluxModulusTransverse planeGlass fiberElastic modulusMolding (decorative)ThermalHeat transferStructural engineeringMechanics

Abstract

fetched live from OpenAlex

Abstract Multi‐layered samples of 1) continuous fiber axially aligned and 2) random oriented mat glass fiber composites were manually prepared for a fiber content ranging from zero to 20% (vol.). The uniaxially aligned samples displayed linear relations between both normalized elastic modulus and normalized thermal conductivity, and fiber content, for axially applied load and heat flux. For the random mat composite samples, similar results were obtained, with symmetry displayed in the plane of the mat. In both cases, measured axial thermal conductivity permits an evaluation of the axial elastic modulus. The Mathis surface probe used (US patent #5,795,064) is demonstrated as a non‐intrusive indirect method of obtaining thermal conductivity for heat flux parallel (i.e. axial or transverse) to the plane of a sample. The method shows potential for use as an in‐line monitoring device for the mechanical properties of molded composites.

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)0.000
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 score0.130
Threshold uncertainty score0.492

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 head0.013
GPT teacher head0.162
Teacher spread0.148 · 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