Comparison of Energy Expenditure during Walking between Female Athletes and Non-Athletes
Bibliographic record
Abstract
This study aimed to determine, if there is a difference in energy expenditure during walking among athletes and non-athletes at two different speeds of walking. Ninety five healthy female students (47 athletes and 48 non-athletes) with a mean age of 22.4 (±1.6) years purposively participated in this study. Medical and sport participation history of the subjects was acquired through a questionnaire. Two experimental tests including anthropometric measurements, VO2max, and walking tests on treadmill at speeds of 3.00 and 3.5 mph were conducted. Results showed no difference in weight, height, body mass index, and leg length between both groups. The non-athletes expended a greater amount of energy than athletes (3.78±.1 and 2.95±.6 kcal.min-1, respectively) at both speeds of 3.00mph and 3.5mph (4.89±1 and 3.94±.7 kcal.min-1). Based on energy requirements for walking at similar weights and speeds by ACSM’s guideline, the female athletes walked at a slow, moderate and brisk pace. Most of the female non-athletes walked at a moderate, brisk and very brisk pace. This study revealed that regular exercise could improve walking efficiency, and the energy expenditure of walking would play an important role in the information processing for total energy requirement that progressively affects weight management and health.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".