Does Altitude of Birth Influence the Performance of National- to Elite-Level Colombian Cyclists?
Bibliographic record
Abstract
OBJECTIVE: To determine whether the altitude of birth/childhood influences the values in peak power output (PPO) and estimated maximum oxygen uptake (estVO2max) in male Colombian road cyclists of different performance levels. This study also aimed to determine whether cyclists born at high altitudes tend to be more successful. METHODS: Eighty riders aged between 17 and 22 years of 3 performance levels (U23 world-class level, WC, n = 8; U23 national level, N23, n = 41; junior national level, J, n = 31) and 3 altitude levels (<800 m, low; 800-2000 m, moderate; >2000 m, high) performed an ergocycle maximal incremental test to exhaustion at an altitude of 2570 m. RESULTS: Altogether, while cyclists born at an altitude >2000 m represented ∼50% of the analyzed sample, there was a significantly higher proportion (84%) of these cyclists who had participated as professionals in a Grand Tour (χ2[1, N = 80] = 4.58, P < .05). Riders of the low group had lower values of PPO and estVO2max than cyclists of moderate and high altitudes, while no differences were noted between moderate- and high-altitude groups. In N23, PPO and estVO2max were lower in the low- than in the moderate-altitude group, while in the J cyclists, PPO and estVO2max were lower in the low-altitude compared with both moderate- and high-altitude groups. DISCUSSION: Among the cyclists tested at altitude in junior and U23, there is an overrepresentation of individuals who reached an elite level and were born at a high altitude (>2000 m). As no clear differences were observed between moderate- and high-altitude cyclists, the higher prevalence of elite cyclists in the latter group may originate from various-still unclear-mechanisms.
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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 | 0.000 | 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) | 0.003 | 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".