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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 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 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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.929
Threshold uncertainty score0.239

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 head0.110
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