Metabolic responses to a loaded movement training workout
Bibliographic record
Abstract
BACKGROUND: Few studies have investigated the metabolic demands of functional exercise. We determined the oxygen cost, heart rate (HR) response, and energy expenditure (EE) both during and immediately following a loaded movement training (LMT) workout. METHODS: Ten participants (5 male, age 23.5±3.7 years, VO2peak 53.3±6.4 mL/kg/min) completed baseline resting metabolic rate testing, a maximal oxygen uptake (VO2) test, and a familiarization trial. After 48 hours' rest, participants completed a 19-minute LMT protocol using functional exercise equipment, consisting of 10 x 60-second work intervals followed by 60 seconds of rest. VO2, HR, respiratory exchange ratio (RER), and EE were measured during the entire LMT protocol and for 45 minutes post-exercise. RESULTS: Participants had a mean VO2 of 65.3±4.1% VO2peak, HR of 91.8±4.0% HRmax, RER of 1.06±0.06, EE of 13.0±3.0 kcal/min (0.176±0.021 kcal/kg/min), and rating of perceived exertion of 17.3±1.6. The mean overall caloric expenditure was 247 kcal. Post-exercise metabolic recovery data showed a mean overall excess post-exercise oxygen consumption (EPOC) of 7.89±3.78 L. EE remained elevated through 15 minutes, VO2 through 30 minutes, and HR through 45 minutes (P<0.05). RER remained depressed throughout the 45-minute collection (P<0.05). CONCLUSIONS: LMT meets the American College of Sports Medicine's recommendations for improving cardiovascular fitness and achieving the daily caloric expenditure from exercise. It may be used to improve cardiovascular fitness and body composition in healthy adults.
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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 | 0.000 | 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 | 0.000 |
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".