Ontogenetic and static allometry in the human face: Contrasting Khoisan and Inuit
Bibliographic record
Abstract
OBJECTIVES: Regional differences in modern human facial features are present at birth, and ontogenetic allometry contributes to variation in adults. However, details regarding differential rates of growth and timing among regional groups are lacking. We explore ontogenetic and static allometry in a cross-sectional sample spanning Africa, Europe and North America, and evaluate tempo and mode in two regional groups with very different adult facial morphology, the Khoisan and Inuit. MATERIALS AND METHODS: Semilandmark geometric morphometric methods, multivariate statistics and growth simulations were used to quantify and compare patterns of facial growth and development. RESULTS: Regional-specific facial morphology develops early in ontogeny. The Inuit has the most distinct morphology and exhibits heterochronic differences in development compared to other regional groups. Allometric patterns differ during early postnatal development, when significant increases in size are coupled with large amounts of shape changes. All regional groups share a common adult static allometric trajectory, which can be attributed to sexual dimorphism, and the corresponding allometric shape changes resemble developmental patterns during later ontogeny. DISCUSSION: The amount and pattern of growth and development may not be shared between regional groups, indicating that a certain degree of flexibility is allowed for in order to achieve adult size. In early postnatal development the face is less constrained compared to other parts of the cranium allowing for greater evolvability. The early development of region-specific facial features combined with heterochronic differences in timing or rate of growth, reflected in differences in facial size, suggest different patterns of postnatal growth.
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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 | 0.000 |
| 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) | 0.002 | 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".