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Record W2117077258 · doi:10.1177/1528083707069506

Clothing Air Gap Layers and Thermal Protective Performance in Single Layer Garment

2007· article· en· W2117077258 on OpenAlexaff
Guowen Song

Bibliographic record

VenueJournal of Industrial Textiles · 2007
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsUniversity of Alberta
FundersNorth Carolina State University
KeywordsThermal manikinAir layerClothingAir gap (plumbing)Materials scienceFlash (photography)ThermalComposite materialLayer (electronics)Structural engineeringForensic engineeringThermal insulationEngineeringMeteorologyOptics

Abstract

fetched live from OpenAlex

A three-dimensional body scanning technique is used to measure the air gap layer distribution between different-sized protective garments and the body of a manikin used to evaluate garment thermal protective performance. The influence of fabric material and garment size on the manikin skin-clothing air gap layers existing in single layer thermally protective coveralls is analyzed. Protective performance of these garments is evaluated using the Manikin Thermal Protective Clothing Analysis System. Relationships between the burn patterns, measured on a flash fire manikin and measured manikin-garment air gap layers, are examined. The effects of thermally induced shrinkage as a result of flash fire exposure are discussed in comparisons between single layer protective coverall clothing made with heat resistant fabrics. An established numerical model is used to forecast the dimensions of skin-clothing air gap for optimum thermal protection.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.110
GPT teacher head0.318
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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations191
Published2007
Admission routes1
Has abstractyes

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