Does employment in high risk professions relating to firefighters and emergency workers cause injuries that requires long hospitalization?
Bibliographic record
Abstract
Firefighters and emergency workers are exposed to increased injury risks. The objective of the paper was to find out if such activities cause injuries that require long hospitalization. The files of 137 firefighters in Littoral Mountainous County, Croatia, were examined as well as those of 120 emergency workers in the last decade. The results have shown that on average firefighters were treated in hospitals 1.33 days, and emergency workers 0.018 days, p = .019, p < .05. The firefighters’ sick leave was longer, with a mean 63.91 days compared to emergency workers sick leave mean 22.90 days, but if two firefighters on long sick leave were excluded, the difference between two groups was not significant, p = .256, p > .05. While these injuries result in short hospitalizations time the sick leave time takes longer and requires extensive outpatient physical therapy that burden hospital system. Overall, the amount of medical care time to return these injured workers to duty is large, there is necessity of implementing innovative injury prevention programs.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".