Dental wear in non-adults of Late Bronze Age pastoralists from Middle Volga and Southern Ural regions
Bibliographic record
Abstract
This study analyses dental wear of children and adolescents from the Late Bronze Age kurgans of the Mid-dle Volga and Southern Ural regions (N = 97). The rate of wear in this sample was compared with a Post-Medieval rural sample from Netherlands. A modified Smith’s scale was used, adapted for two sets of teeth. Wear scores were strongly correlated with age, both when analyzing groups of teeth separately and when scores were averaged for each individual. The studied Volga-Ural sample had a significantly higher rate of dental wear com-pared to the rural sample from the Netherlands, due to higher average scores between 7–14 years of age and lower scores below 7 years of age. The observed intersection of regression lines may be either due to biological or methodological causes. In general, there is some trend towards lower level of wear of deciduous teeth in the Volga-Ural sample compared to a few samples from the literature, which is consistent with the hypothesis of lower attrition rates in pastoralists. It is essential to expand comparative data using the same scoring technique, as well as to address a number of methodological issues related to the simultaneous analysis of two sets of teeth.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".