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Record W2408498890 · doi:10.1080/10803548.2016.1181484

Effectiveness of a cooling jacket with reference to physiological responses in iron foundry workers

2016· article· en· W2408498890 on OpenAlexfundno aff
Ashtekar Shirish, Vishal Kapadia, Sanjeev Kumar, SukhDev Mishra, Gyanendra Singh

Bibliographic record

VenueInternational Journal of Occupational Safety and Ergonomics · 2016
Typearticle
Languageen
FieldMedicine
TopicThermoregulation and physiological responses
Canadian institutionsnot available
FundersIndian Council of Medical ResearchNational Institutes of HealthUniversity of Lethbridge
KeywordsHeat stressSkin temperatureFoundryRelative humidityHeart rateMedicineAnimal scienceMetallurgyInternal medicineMaterials scienceMeteorologyBiomedical engineeringBiology

Abstract

fetched live from OpenAlex

Personal cooling garments (PCGs) have gained increased attention in recent years due to heat stress and strain in the working environment. The present study was conducted in hot environments of an iron foundry to evaluate the efficacy of a battery-operated PCG. Twenty-four workers were exposed to climatic conditions of 35.89 ± 1.25 °C, 35% relative humidity during 90-min work with PCG and habitual clothing (HC). Mean weighted skin temperature was significantly lower by 4.84 ± 1.05 °C compared with HC 0.38 ± 1.02 °C (p < 0.05). A statistically significant difference was also observed for 0.492 ± 0.26 g mean sweat loss in the PCG group compared with 0.775 ± 0.42 g in the HC group (p < 0.05). Heart rate, and back and chest skin temperatures were comparatively more reduced in the PCG group compared with the HC group. PCG provides a practical and economical way of alleviating the physiological effects of heat stress when environmental control is not feasible.

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 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)0.000
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 score0.957
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.049
GPT teacher head0.347
Teacher spread0.298 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations24
Published2016
Admission routes1
Has abstractyes

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