Effects of Group Running on the Training Intensity Distribution of Collegiate Cross-Country Runners
Bibliographic record
Abstract
ABSTRACT: Farrell III, JW, Dunn, A, Cantrell, GS, Lantis, DJ, Larson, DJ, and Larson, RD. Effects of group running on the training intensity distribution of collegiate cross-country runners. J Strength Cond Res 35(10): 2862-2869, 2021-Collegiate cross-country training is often conducted and prescribed in a group setting. This may result in the application of an inappropriate training stimulus to athletes due to potentially different physiological responses to the same training prescription. The aim of this investigation was to quantify the training intensity distribution (TID) of a collegiate cross-country team and the associated physiological adaptions. Sixteen subjects, 8 male subjects and 8 female subjects, performed a graded exercise test before and after observational period to determine peak oxygen consumption (V̇o2peak), the speed (S@), heart rate (HR@), and oxygen consumption (V̇o2@) associated with 2 and 4 mmol·L-1 of blood lactate. Training intensity distribution was quantified by assessing time spent in 3 intensity zones calculated as zone 1 (low intensity, HR values HR@2 and HR@4). No statistical differences were observed between male subjects and female subjects for percent of training time spent in zones 1, 2, and 3. No significant interactions were observed between sex and time for performance variables. Male subjects and female subjects improved V̇o2peak, S@4, and V̇o2@4 with male subjects also increasing V̇o2@2. No significant differences were observed between male subjects and female subjects when comparing percent changes for variables. Examining individual data showed that 2 female subjects experienced performance decrements and trained proportionally more in zones 2 and 3 compared with the overall group. The TID and performance decrements of the 2 highlighted subjects suggest that conducting training in a group setting may potentially be detrimental for some collegiate runners.
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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".