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How Clean is Clean Enough? Maintaining Thermal Protective Clothing Under Field Conditions in the Oil and Gas Sector

2004· article· en· W1486993754 on OpenAlex
Elizabeth M. Crown, Aifen Feng, Xia Xu

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

VenueInternational Journal of Occupational Safety and Ergonomics · 2004
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsLaundryIgnition systemWaste managementClothingCombustionEnvironmental scienceClean-upClean energyPulp and paper industryEngineeringEnvironmental engineeringChemistryChromatography

Abstract

fetched live from OpenAlex

The purpose of this research was to develop practical care procedures to help maintain the protective quality of flame resistant workwear laundered by workers in the field. Based on observed field conditions, experiments were conducted that simulated domestic laundry procedures. The first experiment involved two flame resistant (FR) fabrics, contaminated or not contaminated with oil. Independent variables also included detergent type and laundry pre-treatment. Other laundry parameters were controlled. Results indicated that it is easier to maintain the FR performance of the FR-treated blend than it is for the aramid fabric. It is hypothesized that energy generated by initial ignition of oil on the specimens triggers the FR mechanism of the treatment, which in turn inhibits further combustion. A second experiment using larger specimens and a domestic washing machine also supported the hypothesized mechanism.

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 score0.875
Threshold uncertainty score0.330

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 communication0.0000.001
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 head0.032
GPT teacher head0.301
Teacher spread0.268 · 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