MétaCan
Menu
Back to cohort
Record W2155461041 · doi:10.1177/0040517512468809

Effect of an air gap on the heat transfer of protective materials upon hot liquid splashes

2013· article· en· W2155461041 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTextile Research Journal · 2013
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsMaterials scienceDistilled waterComposite materialMass transferThermalHeat transferAir permeability specific surfaceLayer (electronics)ChemistryChromatographyThermodynamics

Abstract

fetched live from OpenAlex

The thermal protective performance of fabrics against hot liquid splashes was investigated under different configurations. The air gap of 6 mm between specimen and sensor was simulated and compared with direct contact configuration. Three liquids (distilled water, canola oil, drilling mud) at 85℃ were applied as challenge hot liquid hazards. The results showed that fabric permeability significantly affected heat transfer due to the occurrence of mass transfer both with and without a spacer. The absorbed energy and second-degree burn time presented significantly negative correlation. The effect of air gap on thermal performance was investigated. The findings demonstrated that minimizing mass transfer could effectively improve thermal protection against hot liquid splashes and the existing of an air layer could improve thermal performance.

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)0.012
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.020
Threshold uncertainty score0.980

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0210.001

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 head0.073
GPT teacher head0.377
Teacher spread0.304 · 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