Pacing in age-group freestyle swimmers at The XV FINA World Masters Championships in Montreal 2014
Bibliographic record
Abstract
Pacing strategies have been investigated for elite-standard freestyle swimmers, but little is known about pacing in age-group freestyle swimmers. We investigated changes in swimming time across distances in 4,481 women and men swimmers who competed in 100, 200, 400, and 800 m freestyle age groups from 25–29 years to 90–94 years in the FINA World Masters Championships 2014. In 100 to 800 m, there was a small lap×sex interaction (P < 0.001, 0.033 ≤ η2 ≤ 0.045) whereby women had larger lap-to-lap changes in swimming time than men. From 100 to 800 m, there were moderate to large lap×age group interactions (P < 0.001, 0.054 ≤ η2 ≤ 0.235), i.e., pacing patterns differed by age groups. There were small main effects of lap on time in 100, 200, 400 and 800 m freestyle events (P < 0.001, 0.033 ≤ η2 ≤ 0.045). In summary, (i) the largest increase in swimming time occurred during the second lap and a decrease in time occurred during the last lap, except in the 100 m, and (ii) the effect of participants’ sex on lap time indicated larger percentage changes of pacing in women than in men. These findings should help coaches to develop age- and event-tailored pacing strategies.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".