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Record W419036459 · doi:10.1177/0021998315583924

Void and porosity characterization of uncured and partially cured prepregs

2015· article· en· W419036459 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 Composite Materials · 2015
Typearticle
Languageen
FieldEngineering
TopicEpoxy Resin Curing Processes
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials sciencePorosityComposite materialVoid (composites)PolishingOptical microscopeCuring (chemistry)EpoxyScanning electron microscopeCharacterization (materials science)

Abstract

fetched live from OpenAlex

Void characterization and porosity measurements of uncured and partially cured carbon/epoxy prepregs are challenging due to the soft nature of the matrix. If samples need to be cut from a larger laminate, the act of cutting and polishing can alter the void morphology. This paper presents a method to prepare samples for optical microscopy by infiltrating the pore space in the soft prepreg with a room-temperature curing low-viscosity resin to support the structure during cutting and polishing in preparation for optical microscopy. The methodology is validated by comparison with results obtained from porosity measurements using the ASTM D2734 standard density method. The paper also explores the use of thickness measurements to determine porosity. It is shown that thickness measurements can be used to estimate porosity for the no-bleed out-of-autoclave prepreg system used in the present study but that the accuracy is lower than using microscopy or density methods.

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 score0.053
Threshold uncertainty score0.338

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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