Variability in performance on a work simulation test of physical fitness for firefighters
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 Canadian Forces Firefighter Physical Fitness Maintenance Evaluation (FF PFME) requires firefighters in full fire-protective ensemble, including self-contained breathing apparatus, to correctly complete 10 work-related tasks on a measured and calibrated course. Fitness for duty is inferred from completion time of the course. We hypothesized that completion time may be dependent on pacing strategy and day-to-day fluctuations in biological function. To examine variability in performance, 20 females and 31 males (mean ± SD; age, 27.6 ± 10.5 years; height, 176.7 ± 8.3 cm; mass, 77.3 ± 13.4 kg) were familiarized with the FF PFME and then completed the test on 6 separate days. Pre-test behaviours (e.g., sleep, diet) and test conditions (e.g., calibration, time of day) were consistent. Repeated-measures ANOVA revealed a significant decrease in completion time between tests 1 and 6 (18.7%) and between all sequential pairs (e.g., tests 1 and 2). There was also a small but significant increase in the fraction of total test time for task completion and a corresponding decrease in the time to transition between tasks. The performance improvements cannot be explained by differences in effort (heart rate and perceived exertion). Coefficient of variation for tests 1, 2, and 3 was 7% and for tests 4, 5, and 6 was 2.6%. The results indicate the importance of practice on performance and the potential for false-positive or false-negative decision errors if biological variability is not taken into account.
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) | 0.000 | 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