Biofeedback Reaction-Time Training: Toward Olympic Gold
Bibliographic record
Abstract
As part of a larger training program, applying a new biofeedback protocol for improving reaction time (RT) performance among elite speed skaters at the Canadian Speedskating National Training Center in Montreal, Canada, provided an advantage at the Vancouver 2010 Olympic Games, allowing athletes to assert themselves and claim the best starting position during the event. Each athlete participated in a twice-weekly biofeedback RT training for 5 weeks, for a total of 600 RT practice trials, simulating speed-skating activities such as reacting to commands of “go to the start,” “ready,” and the sound of a signal from a gun to start. There was an overall improvement in RT performance from the beginning to the end of the 5-week period, with the largest improvement occurring between Weeks 4 and 5 of the training, F (1, 9) = 679.2, p = .001. The results suggest that biofeedback protocols will become an essential part of a winning strategy for future interventions in speed skater 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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".