Oxygen cost of the CF–DND fire fit test in males and females
Bibliographic record
Abstract
The Department of National Defence employs a work-related test circuit comprising 10 various firefighting tasks (FF test) to assess the fitness of incumbent Canadian Forces firefighters. The main purpose of this study was to document the oxygen cost of the FF test over a wide range of performance times. These data were then used to predict the oxygen cost associated with the 8 min completion standard. Finally, we examined the influence of gender on selected physiological responses during the FF test. Thirty male and 23 female subjects practiced the test 3-5 times and then completed, in random order and on separate days, a maximal-effort trial while breathing with either a self-contained breathing apparatus (SCBA) or a portable metabolic measurement system (MMC). The breath-by-breath gas exchange data from the MMC were collapsed into a single value that represented the average oxygen cost for each participant to complete the work simulation. To calculate the average VO2 associated with the 8 min completion time, separate regression lines for test duration and average VO2 were generated for males and females. Analyses of covariance (ANCOVA) revealed that the regression lines for the male and female groups coincided, therefore all data were collapsed. The resulting regression equation predicted that the average VO2 associated with the 8 min standard was 34.1 (+/-4.0) mL.kg(-1).min(-1), and this value appears consistent with other research on the oxygen cost of firefighting. There was no evidence to suggest that the oxygen cost of meeting the 8 min standard was different for males or females.
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.
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 | 0.000 | 0.002 |
| 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) | 0.003 | 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".