Training periodization and competition management in Surf Clube de Viana development team
Bibliographic record
Abstract
This report presents the internship reports that took place in Surf Clube de Viana with a six months duration. The objectives were to access, monitor, and improve the performance of young surf athletes, understand the management process, and plan the sports season and training plan. The report is divided into two parts. The first part explains the problem supported by recent literature, and it clarifies what is Surfing and what is Surfing performance. The second part is a practical report of the internship activities, showing the surf performance analysis and planning of the competitive surf season. This second part also have an investigation in to practices with the objective to understand the relationship between basic psychological needs and mental toughness and the influence of gender, age, and years of sporting experience on mental strength. This internship allowed the development of ground abilities connected to planning and executing a training cycle for a particular preparation period and competing surf seasons. The tasks during the internship were diverse, and it started with the physical evaluation of athletes and went through planning the training units, monitoring the athletes' performance, providing feedback, and enhancing improvement of their capacities. It deepened the knowledge of the surfing field, its techniques, and tactics, to being able to provide more comprehensive feedback to the athletes and accomplishing all the tasks concerning performance in surfing training.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".