Genomic scan for maximal oxygen uptake and its response to training in the HERITAGE Family Study<sup>*</sup>
Bibliographic record
Abstract
This study aimed to identify human genomic regions that are linked to maximal oxygen uptake (VO(2 max)) in sedentary individuals or to the responsiveness of VO(2 max) to a standardized endurance training program. The results of a genomic scan based on 289 polymorphic markers covering all 22 pairs of autosomes performed on the Caucasian families of the HERITAGE Family Study are presented. The mean spacing of the markers was 11 cM, and a total of 99 families and 415 pairs of siblings were available for the study. VO(2 max) in the sedentary state was adjusted for the effects of age, sex, body mass, fat mass, and fat-free mass, whereas the VO(2 max) response was adjusted for age and baseline level of the phenotype. Two analytic strategies were used: a single-point linkage procedure using all available pairs of siblings (SIBPAL) and a multipoint variance components approach using all the family data (SEGPATH). Results indicate that linkages at P values of 0.01 and better are observed with markers on 4q, 8q, 11p, and 14q for VO(2 max) before training and with markers on 1p, 2p, 4q, 6p, and 11p for the change in VO(2 max) in response to a 20-wk standardized endurance training program. These chromosomal regions harbor many genes that may qualify as candidate genes for these quantitative traits. They should be investigated in this and other cohorts.
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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 | 0.001 | 0.001 |
| 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) | 0.004 | 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".