A Comparison of Fitness Training to a Pedometer-Based Walking Program Matched for Total Energy Cost
Bibliographic record
Abstract
BACKGROUND: Fitness and health variables were measured in 128 sedentary men and women randomly assigned to 6 months of fitness training (F), a walking program (W), or a control (C) group. METHODS: The F program gradually increased volume and intensity until 4 d/wk of training, at 70% of peak VO2 for 43 min/session was prescribed while the W group performed daily walking monitored with pedometers and increased until 10,000 steps x d-1 were prescribed. Total weekly energy expenditure was matched between the activity groups. The control group was asked to maintain their usual activity. RESULTS: Body mass, waist circumference, waist/hip ratio, resting HR were reduced in all groups after 6 months (P < .05). Fasting glucose, glucose tolerance, and total cholesterol were similarly improved in all groups (P < .05). Blood pressure and HR decreased during submaximal exercise in all groups (P < .05) but rating of perceived exertion (RPE) was decreased only in the F group (P < .05). Only the F participants showed a significant increase in ventilatory threshold (VT; ~15%) and peak VO2 (~9%) after 6 months. CONCLUSIONS: Supervised fitness training in previously sedentary adults produced greater improvements in submaximal RPE, BP(sys), VT, and peak VO2 but not other fitness and health-related variables compared with a pedometer-based walking program matched for total energy cost.
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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) | 0.001 | 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) | 0.001 | 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".