Evaluation of cognitive performance and fatigability under hypoxia in elite youth athletes
Bibliographic record
Abstract
The goal of this study was to compare fatigability in hypoxia (3500 m) vs normoxia in elite youth athletes. We aimed also to validate a newly developed and open-access iOS app for the evaluation of cognitive performance in the field. This work is part of the “Québec Freestyle Ski Neurophysiological Optimization (QueFreSkiNO) Project”, aiming at improving fatigue monitoring, sleep habits, and performance in athletes of the Quebec national teams of freestyle ski, with a particular focus on hypoxia exposure. The project procedures follow provincial regulations, the Declaration of Helsinki (2013), and the intention-to-treat principle. The testing procedures have been further approved by the CIUSSS du Nord-de-l’Île-de-Montréal Ethical Research Committee (n. 2024-2718). The present repository contains all data and analysis of the 2 studies performed to address the research goal. Link to the OA paper: https://doi.org/10.1371/journal.pone.0353673
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".