Population Differences of Nasofrontal Angle Expression: A Coordinate‐Based Study
Bibliographic record
Abstract
The nasofrontal angle has long been studied within the context of rhinoplasty and aesthetic surgery. However, few have observed the distribution of this trait over clinal zones ranging from temperate to tropical latitudes. This study tests the relationship between climate and nasofrontal angle on a sample (n=130) of dry crania from geographically diverse human populations. The nasofrontal angle was calculated from coordinate data collected among the landmarks glabella, nasion, and rhinion. Specimens of both sexes were used so that the maximum range of variation could be expressed in each population, thus allowing for a more stringent analysis. It was found that northern and southern Europeans are not significantly (p<0.05) different from each other or from North Africans and South East Asians. However, they possessed significantly (p<0.05) smaller (i.e., more acute) angles than the Inuit, Chinese, and East and West African samples, which did not exhibit any significant differences among each other or from the North Africans and South East Asians. Nasofrontal angle may share a closer relationship with nasal projection than climate as leptorrhine Europeans possess the most acute angles. However, the results may indicate separate population histories of Europeans and Inuit who, despite both inhabiting relatively northerly latitudes, developed separate adaptations to cold climate. Grant Funding Source : SUNY Downstate College of Medicine
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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) | 0.002 | 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".