Bibliometric analysis of occupational health in civil construction works
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
Objective: to perform a bibliometric analysis of occupational health in civil construction works in areas of focus and significant contributions in the last 10 years (2013-2023) worldwide indexed in Scopus. Methodology: A quantitative bibliometric analysis was undertaken. The indicators of scientific waste were generated by means of 100 documents selected in Scopus using the keywords in English ("occupational health" AND "civil construction") from 2013 to 2023.Results: There was a 27.90% growth in publications on the subject by the year 2020, which indicates a strong interest in the subject. Portugal is one of the countries with more scientific production (n=74; 20.67%), and the University of Lisbon with more publications (n=14). The journal Material Science and Engineering: R Reports received 96 citations with the author being Salas, J. Conclusions: The bibliometric analysis of occupational health in civil construction works during the last 10 years (2013-2023) has provided valuable insight into the areas of focus and significant contributions in this field. The data reveal a steady increase in research output, with a notable peak in the period studied. It has been observed that several nations, including Portugal, Canada and Mexico, have contributed significantly to the scientific output in this field.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.095 | 0.274 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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