Determining the level of physical activity estimated by the Canada Fitness Survey questionnaire using criteria of the InternationalPhysical Activity Questionnaire
Bibliographic record
Abstract
Summary Study aim: The aim of the study was to determine the weekly energy expenditure measuring MET/min/week based on data collected through the Canada Fitness Survey (CFS), according to the classification used in the International Physical Activity Questionnaire (IPAQ), and to verify the adopted method to assess the level of physical activity in students of physical education. Material and methods: The study involved 116 female students (21.1 ± 1.6) and 276 male students (21.2 ± 1.7), studying Physical Education at Kazimierz Wielki University. Physical activity (PA) of respondents assessed using the Canada Fitness Survey was converted to energy expenditure in MET/min/week using the criteria established in the IPAQ. Body composition was assessed according to bioelectrical impedance. Results: A significantly smaller fat fraction was observed in the group of students with high physical activity (PA) (p < 0.01). In women, there was a significant relation between FAT% and all analysed characteristics of physical activity: total physical activity (TPA) – 0.274, vigorous intensity (VI) – 0.216, number of days spent on physical activity (DTPA) – 0.199 and number of days spent on vigorous intensity (DVI) – 0.202 (p < 0.05). In men, a significant relation was found between all the analysed tissue components and the adopted variables of PA (FAT% vs. TPA – 0.145, VI – 0.203, DTPA – 0.187; FATkg vs. TPA – 0.123, VI – 0.186, DTPA – 0.178; FATkg vs. DVI – 0.131). BMI significantly correlated with VI (–0.162) and DVI (–0.140), p < 0.05. Conclusions: Based on data collected using the CFS on the type and frequency of PA during a week, we can determine the level of activity in a measurable way, using the IPAQ classification. There is a significant relationship between thus determined physical activity levels and body composition in both women and men, which proves the accuracy of the adopted method of converting weekly energy expenditure to MET/min/week.
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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 | 0.001 |
| 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) | 0.002 | 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".