Efficacy of downhill running training for improving muscular and aerobic performances
Bibliographic record
Abstract
This study investigated effects of downhill (DR) versus level (LR) running training on various muscular and aerobic performances. Eighteen healthy young males conducted either DR (DR group (DRG), n = 10: –10% slope) or LR (LR group (LRG), n = 8) training at a target heart rate (HR) associated with lactate threshold (LT) for 20 min·session −1 , 3 sessions·week −1 , for 5 weeks. Before and after the interventions, the following variables were measured: knee extension torque (–150, –30, 0, 30, 150°·s −1 ), leg extension power (simultaneous hip and knee extension: 0.8 m·s −1 ), squat and countermovement jump height, rebound jump index (jump height·contact time −1 ), 20-m linear sprint and change-of-direction (Pro-agility and V-cut tests) time, and aerobic capacity (maximal oxygen uptake, energy cost at LT, and velocity at maximal oxygen uptake and LT) on a level surface. Throughout the training sessions, HR during running did not differ between the groups (DRG: 77.7% ± 4.6% vs LRG: 76.4% ± 4.6% of maximal HR; average across all sessions), while velocity was significantly higher for DRG (14.5 ± 1.1 vs 12.0 ± 1.9 km·h −1 ). After the training, DRG significantly improved knee extension torque at all angular velocities (9%–24%) and change-of-direction time for both tests (2%–3%), with no changes in other parameters. LRG significantly improved maximal oxygen uptake (5%), energy cost at LT (3%), and velocity at maximal oxygen uptake (7%), without changes in others. These results suggest that DR training has a greater potential to improve the knee extension strength and change-of-direction ability, but has little effect on the aerobic capacity, compared with HR-matched LR training.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".