Tracing intensive fish and meat consumption using Zn isotope ratios: evidence from a historical Breton population (Rennes, France)
Bibliographic record
Abstract
Abstract Here we report Sr and Zn isotope ratios of teeth of medieval to early modern Breton people a population whose diet is known from historical, archeological and collagen isotope data. Most of the population, buried in the Dominican convent of Rennes, France, consists of parliamentary nobles, wealthy commoners and ecclesiastics, who had a diet rich in animal products. Our aim is to assess how the Zn isotope ratios of their teeth compare to those of other French historical populations previously studied, which were characterized by cereal-based diets, and those of modern French individuals, who daily eat animal products. We describe a clear offset (∼0.35‰) between local and non-local human individuals in Zn isotope ratios. The δ66Zntooth values of local individuals overlap that of modern French people, and are lower than those of local carnivores. Non-local δ66Zn values are similar to those of historical individuals analyzed previously. We conclude the lower Zn isotope ratios of local humans relative to the associated fauna can be explained by the consumption of carnivorous fish and pork, in agreement with historical, zooarchaeological and collagen (C, N, S) isotope data. Zn isotopes could therefore be a tracer of fish and/or substantial meat consumption in ancient populations.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".