Surname‐Inferred andean ancestry is associated with child stature and limb lengths at high altitude in <scp>P</scp>eru, but not at sea level
Bibliographic record
Abstract
OBJECTIVES: Native Andean ancestry gives partial protection from reduced birthweight at high altitude in the Andes compared with European ancestry. Whether Andean ancestry is also associated with body proportions and greater postnatal body size at altitude is unknown. Therefore, we tested whether a greater proportion of Andean ancestry is associated with stature and body proportions among Peruvian children at high and low altitude. METHODS: Height, head circumference, head-trunk height, upper and lower limb lengths, and tibia, ulna, hand and foot lengths, were measured in 133 highland and 169 lowland children aged 6 months to 8.5 years. For highland and lowland groups separately, age-sex-adjusted anthropometry z scores were regressed on the number of indigenous parental surnames as a proxy for Andean ancestry, adjusting for potential confounders (maternal age and education, parity, altitude [highlands only]). RESULTS: Among highland children, greater Andean ancestry was negatively associated with stature and tibia, ulna, and lower limb lengths, independent of negative associations with greater altitude for these measurements. Relationships were strongest for tibia length: each additional Andean surname or 1,000 m increase at altitude among highland children was associated with 0.18 and 0.65 z score decreases in tibia length, respectively. Anthropometry was not significantly associated with ancestry among lowland children. CONCLUSIONS: Greater Andean ancestry is associated with shorter stature and limb measurements at high but not low altitude. Gene-environment interactions between high altitude and Andean ancestry may exacerbate the trade-off between chest dimensions and stature that was proposed previously, though we could not test this directly.
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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) | 0.002 | 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".