Association Between Reactive Strength Index and Metabolic Cost of Running in Male Master Athletes
Bibliographic record
Abstract
PURPOSE: To examine the association between reactive strength index (RSI) and metabolic cost of running (MCr) in master athletes. We hypothesized that individuals with a higher RSI would exhibit a lower MCr, that both variables would be associated, and that age would moderate this relationship. METHODS: Forty-five male master athletes participated to this study. A median split was performed to constitute 2 age groups (group 1, 47.7 [1.7] y old; group 2, 56.3 [4.6] y old). Participants underwent a single 45-minute session during which RSI was assessed with drop jumps, and MCr, during a continuous exercise of submaximal intensity performed on a treadmill. RESULTS: A small negative association was found between net MCr and RSI in the overall sample (RSI mean r = -.38, P < .05; RSI max r = -.38, P < .05). Group 1 exhibited a lower net MCr (P < .01, d = -0.84) and higher RSI (P < .01, d > 0.82) than group 2. However, the association between the 2 measures was verified specifically in group 2 (RSI from a 20-cm drop jump, r = -.53, P < .01; RSI mean, r = -.50, P < .05; RSI maximum, r = -.57, P < .01). CONCLUSIONS: RSI is associated with net MCR in master athletes, particularly in older participants. Additional intervention studies are now required to further explore this association.
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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) | 0.002 | 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".