Haematological changes in elite kayakers during a training season
Bibliographic record
Abstract
This study monitored haematological markers in response to training load in elite kayakers during a training season. The sample comprised eight elite kayakers aged 22 ± 4.2 years with a 77.2 ± 6.7 kg body mass and a 177.5 ± 5.6 cm stature. The initial [Formula: see text]O(2max) was 61.2 ± 5.5 mL·kg(-1)·min(-1). The control group consisted of six healthy males, aged 18.6 ± 1.1 years, with an 81.3 ± 13.8 kg body mass and a 171.9 ± 4.5 cm stature. Blood samples were collected at the beginning of the training season after an off-training period of six weeks (t(0)), at the 11th week after the application of high training volumes (t(1)), at the 26th week after an intense training cycle (t(2)), and at the 31st week at the end of a tapering phase (t(3)). Differences between time points were detected using ANOVA and the Bonferroni post hoc test. Significant changes were found after the intense training cycle (t(2)), lymphocytes decreased while haemoglobin, mean corpuscular volume, mean corposcular haemoglobin, mean concentration of corpuscular hemoglobin concentration, platelets distribution width, and red blood cell distribution width values increased when compared with baseline values. At t(3), a reduction in monocyte numbers and an increase in mean platelet volume compared with baseline values were seen. By reducing the volume and intensity of training, many variables returned to values close to those at baseline. Although many athletes had accumulated responses over time due to training, they still suffered transient changes that appear to be influenced by training load. Haemorheology monitoring may help detect health risks, especially during times of intensified 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".