Comparative study of fetal facial shape between Japanese and North American populations using micro-CT
Bibliographic record
Abstract
Population-level morphological differences in human cranio-skeletal morphology are reflective of a multitude of genetic, epigenetic, functional and environmental factors. While such differences have been described in postnatal and adult skeletons, how early they originate during cranio-skeletal ontogeny is unknown. Here we compare early human facial morphogenesis utilizing a collection of fetal specimens of Japanese (JP) and North American - European ancestry (NAP). Utilizing 3D micro-CT images and geometric morphometric analyses, we have identified subtle, yet significant differences in the morphology of the upper and midfacial regions in fetuses in the second trimester of gestation. Notably, the orbital rims and lateral areas of the zygomatic bones in the JP specimens have more prominent superior and inferior orbital rims, with a more prominent lateral project of the zygomatic bone, compared to the NAP. These data suggest that the cranioskeletal structures display early facial patterning unique to genealogically distinct populations. Since these specimens are derived from very early developmental stages, the impacts of functional factors are expected to be minor, while inherited genetic and epigenetic programming predominate in driving the observed morphological differences.
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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".