Dental calculus in the industrial age: Human dental calculus in the Post-Medieval period, a case study from industrial Manchester
Bibliographic record
Abstract
The analysis of dental calculus (mineralised dental plaque) has become an increasingly important facet of bioarchaeological research. Although microscopic analysis of microdebris entrapped within dental calculus has revealed important insights into the diet, health, and environment of multiple prehistoric populations, relatively few studies have examined the contributions of this approach to more recent historical periods. In this study, we analyze dental calculus from an English Post-Medieval, middle-class urban skeletal assemblage from Manchester, England using light microscopy. We characterize all types of microremains, observing heavily damaged starch and plant material, high quantities of fungal and yeast spores, the presence of wood particles, plant (cotton) and animal (wool) fibres, as well as limited quantities of microcharcoal and burnt debris. We observe the presence of non-native, imported plant products, including New World maize and potentially tapioca starch. We compare our results to similar studies from earlier time periods to reveal the impacts of the significant economic, social and environmental changes occurring during the Industrial period in England, including changes in food processing, food access, food storage, and air quality. We conclude by outlining important methodological considerations for the future study of Post-Medieval dental calculus and propose potential areas of future research.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".