Distribution of Number, Location of Pain and Comorbidities, and Determinants of Work Limitations among Firefighters
Bibliographic record
Abstract
INTRODUCTION: The unique demands of firefighting results in acute, recurrent, or chronic pain complications. We aimed to describe the percentage distribution of number and location of painful sites among FFs and determine whether work limitations differed based on the number or location of painful sites, age, and/or sex. METHODS: About 325 firefighters completed a work limitation questionnaire (WLQ-26) and a checklist to indicate painful regions of the body using either a paper format or an online survey. A one-way ANOVA was employed to analyze the transformed work limitation scores; this was a two-sided test with a significance level of <0.05, to determine if work limitations differed among firefighters based on the number or location of painful sites, age, and/or sex. RESULTS: = 0.008). CONCLUSIONS: The majority of firefighters reported having at least one painful site and indicated the spine as the most common painful location. Age, the number of painful sites, and location of pain were identified as a potential contributor to physical/mental and work output limitations.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".