Familial resemblance for physique: heritabilities for somatotype components
Bibliographic record
Abstract
PRIMARY OBJECTIVE: To examine familial resemblance in the Heath-Carter anthropometric somatotype in a sample of 328 participants from 103 nuclear families in Northern Ontario (Canada). METHODS AND PROCEDURES: The three somatotype components (endomorphy, mesomorphy, ectomorphy) were subjected to principal components analysis and the resulting first principal component (PCI) was used as an additional index of physique. The four phenotypes were adjusted for age, sex and generation effects, while each of the three somatotype components was further adjusted for the effects of the other two components using regression procedures. A familial correlation model was fit to the data and used to estimate the degree of familial resemblance in somatotype. MAIN OUTCOME AND RESULTS: For all somatotype variables, the most parsimonious model was one in which there was no spouse resemblance and no sex or generation effects in the familial correlations. Maximal heritabilities were 56%, 68%, 56% and 64% for endomorphy, mesomorphy, ectomorphy and PCI, respectively, indicating significant familial resemblance for the Heath-Carter anthropometric somatotype. Further, the pattern of familial correlations suggests the role of genetic factors in explaining variation in human physique. CONCLUSIONS: In general, a pattern of no spouse but significant parent-child correlations implicates the role of genes on human physique, provided that mating is random with regard to these traits.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| 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".