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Record W1592357381 · doi:10.1177/155892500700200204

Application of Nanofiber Technology to Nonwoven Thermal Insulation

2007· article· en· W1592357381 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 Engineered Fibers and Fabrics · 2007
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMaterials scienceNanofiberComposite materialThermal insulationPolyacrylonitrileThermal radiationFiberMicrometerThermalThermal transferHeat transferGlass fiberTextilePolymerLayer (electronics)Optics

Abstract

fetched live from OpenAlex

Nanofiber technology (fiber diameter less than 1 micrometer) is under development for future Army lightweight protective clothing systems. Nanofiber applications for ballistic and chemical/biological protection are being actively investigated, but the thermal properties of nanofibers and their potential protection against cold environments are relatively unknown. Previous studies have shown that radiative heat transfer in fibrous battings is minimized at fiber diameters between 5 and 10 micrometers. However, the radiative heat transfer mechanism of extremely small diameter fibers of less than 1 micrometer diameter is not well known. Previous studies were limited to glass fibers, which have a unique set of thermal radiation properties governed by the thermal emissivity properties of glass. We are investigating the thermal transfer properties of high loft nanofiber battings composed of carbon fiber and various polymeric fibers such as polyacrylonitrile, nylon, and polyurethane. Thermal insulation battings incorporating nanofibers could decrease the weight and bulk of current thermal protective clothing, and increase mobility for soldiers in the battlefield.

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 score0.147
Threshold uncertainty score0.214

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 head0.007
GPT teacher head0.259
Teacher spread0.252 · 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