Developing a heat stress model for construction workers
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.
Bibliographic record
Abstract
Purpose Heat stress, having caused preventable and lamentable deaths, is hazardous to construction workers in the hot and humid summers of Hong Kong. The purpose of this paper is to develop a heat stress model, based on the Wet Bulb Globe Temperature (WBGT) index. Design/methodology/approach Field studies were conducted during the summer time in Hong Kong (July to September 2010). Based upon 281 sets of synchronized meteorological and physiological data collected from construction workers in four different construction sites between July and September 2010, physiological, work‐related, environmental and personal parameters were measured to construct and verify the heat stress model. Findings It is found that drinking habit, age and work duration are the top three significant predictors to determine construction workers' physiological responses. Other predictors include percentage of body fat, resting heart rate, air pollution index, WBGT, smoking habit, energy consumption, and respiratory exchange rate. The accuracy of the model is verified against data which have not been used in developing the model. The accuracy of the heat stress model is found to be statistically acceptable (Mean Absolute Percentage Error=5.6 percent, Theil's U inequality coefficients=0.003). Practical implications Based on these findings, appropriate work‐rest pattern can be designed to safeguard the well being of workers when working in a hot and humid environment. Originality/value The model reported in this paper provides a more scientific and reliable prediction of the reality which may benefit the industry to produce solid guidelines for working in hot weather.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it