Isotope analysis of human dental calculus δ <sup>13</sup> CO <sub>3</sub> <sup>2−</sup> : Investigating a potential new proxy for sugar consumption
Bibliographic record
Abstract
Rationale Dental calculus (mineralised dental plaque) is composed primarily of hydroxyapatite. We hypothesise that the carbonate component of dental calculus will reflect the isotopic composition of ingested simple carbohydrates. Therefore, dental calculus carbonates may be an indicator for sugar consumption, and an alternative to bone carbonate in isotopic palaeodiet studies. Methods We utilised Fourier transform infrared attenuated total reflectance analysis to characterise the composition and crystallisation of bone and dental calculus before isotope analysis of carbonate. Using a Sercon 20‐22 mass spectrometer coupled with a Sercon GSL sample preparation system and an IsoPrime 100 dual inlet mass spectrometer plus Multiprep device to measure carbon, we tested the potential of dental calculus carbonate to identify C 4 resources in diet through analysis of δ 13 C values in paired bone, calculus and teeth mineral samples. Results The modern population shows higher δ 13 C values in all three tissue carbonates compared to both archaeological populations. Clear differences in dental calculus δ 13 C values are observed between the modern and archaeological individuals suggesting potential for utilising dental calculus in isotope palaeodiet studies. The offset between dental calculus and either bone or enamel carbonate δ 13 C values is large and consistent in direction, with no consistent offset between the δ 13 C values for the three tissues per individual. Conclusions Our results support dental calculus carbonate as a new biomaterial to identify C 4 sugar through isotope analysis. Greater carbon fractionation in the mouth is likely due to the complex formation of dental calculus as a mineralized biofilm, which results in consistently high δ 13 C values compared to bone and enamel.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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) | 0.001 | 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".