Fish and maize: Bayesian mixing models of fourteenth- through seventeenth-century AD ancestral Wendat diets, Ontario, Canada
Bibliographic record
Abstract
Abstract Freshwater and marine fish have been important components of human diets for millennia. The Great Lakes of North America, their tributaries and smaller regional freshwater bodies are important Native American fisheries. The ethnohistorical record, zooarchaeological remains, and isotopic values on human bone and tooth collagen indicate the importance of fish in fourteenth- through seventeenth-century ancestral Wendat diets in southern Ontario, which is bordered by three of the Great Lakes. Maize ( Zea mays ssp. mays ) was the primary grain of Native American agricultural systems in the centuries prior to and following sustained European presence. Here we report new Bayesian dietary mixing models using previously published δ 13 C and δ 15 N values on ancestral Wendat bone and tooth collagen and tooth enamel. The results confirm previous estimates from δ 13 C values that ancestral Wendat diets included high proportions of maize but indicate much higher proportions of fish than has previously been recognized. The results also suggest that terrestrial animals contributed less to ancestral Wendat diets than is typically interpreted based on zooarchaeological records.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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 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".