Molar size and shape in the estimation of biological ancestry: A comparison of relative cusp location using geometric morphometrics and interlandmark distances
Bibliographic record
Abstract
Human molars exhibit varying shapes when viewed from the occlusal surface. Available methods for quantifying molar occlusal shape have historically been confined to qualitative descriptions. The present study utilized geometric morphometric analyses to capture molar shape as defined through relative cusp locations. Cusp apices of maxillary and mandibular first and second molars were digitized from 190 American Blacks and Whites to estimate biological affinity through the shape of relative cusp locations. The coordinate data were subjected to a Generalized Procrustes Analysis to generate Procrustes coordinates and calculate centroid sizes. Procrustes coordinates were then subjected to a principal component analysis to examine the direction and magnitude of shape change inherent in the sample. Centroid size and major shape component group means were compared with t-tests. Interlandmark distances were then calculated from the raw coordinate information and also subjected to a principal components analysis. Procrustes coordinates and the principal components derived from them with and without centroid size, along with the interlandmark distances and the principal components derived from them, were each subjected to a discriminant function analysis to examine which methods yielded the highest correct classification between population groups. Total correct classifications ranged from 62.7% to 87.9% depending on the variables forward stepwise selected for each analysis. Using a combination of the second maxillary molar and first mandibular molar yielded the most optimistic results and corroborates theoretical models of molar development.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".