Cranial morphological variation among contemporary Mexicans: Regional trends, ancestral affinities, and genetic comparisons
Bibliographic record
Abstract
Genetic research has documented geographical variation within Mexico that corresponds to trends in ancestry admixture from postcolonial times on. The purpose of this study is to determine whether craniometric variation among contemporary Mexicans is comparable to that reported in genetic studies. Standard osteometric measurements were taken on 82 male crania derived from forensic cases, with geographic origins of the specimens spanning over two-thirds of Mexico's states. To study similarities in regional clustering patterns with genetic data, k-means clustering analyses were performed, followed by chi-square tests of association between cluster assignments and geographic region of origin. Normal mixtures analyses were performed, centered on three "ancestral" sample proxies to estimate classification probability to each ancestry. The results demonstrate that the cranial morphological sample data cluster similarly to the regional groupings inferred from the genetic data. Additionally, the results indicate a gradient trend in population structure for contemporary Mexicans, with the proportion of Amerindian ancestry increasing from North to South while, conversely, European ancestry proportion estimates increase from South to North. Furthermore, the probabilities for classification of African ancestry remained low across the regions, again reflecting the results for the genetic data. Cranial morphological variation is well aligned with the genetic data for describing broad trends among Mexican populations, as well as yielding comparable estimates of general ancestry affiliations that reflect Mexico's history of Spanish contact and colonialism.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".