Metabolic energy cost of workers in agriculture, construction, manufacturing, tourism, and transportation industries
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
The assessment of energy cost (EC) at the workplace remains a key topic in occupational health due to the ever-increasing prevalence of work-related issues. This review provides a detailed list of EC estimations in jobs/tasks included in tourism, agriculture, construction, manufacturing, and transportation industries. A total of 61 studies evaluated the EC of 1,667 workers while performing a large number of tasks related to each of the aforementioned five industries. Agriculture includes the most energy-demanding jobs (males: 6.0 ± 2.5 kcal/min; females: 2.9 ± 1.0 kcal/min). Jobs in the construction industry were the 2nd most demanding (males: 4.9 ± 1.6 kcal/min; no data for females). The industry with the 3rd highest EC estimate was manufacturing (males: 3.8 ± 1.1 kcal/min; females: 3.0 ± 1.3 kcal/min). Transportation presented relatively moderate EC estimates (males: 3.1 ± 1.0 kcal/min; no data for females). Tourism jobs demonstrated the lowest EC values (2.5 ± 0.9 kcal/min for males and females). It is hoped that this information will aid the development of future instruments and guidelines aiming to protect workers' health, safety, and productivity. Future research should provide updated EC estimates within a wide spectrum of occupational settings taking into account the sex, age, and physiological characteristics of the workers as well as the individual characteristics of each workplace.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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