Migration and maize in the Virú Valley: Understanding life histories through multi‐tissue carbon, nitrogen, sulfur, and strontium isotope analyses
Bibliographic record
Abstract
Abstract Objectives Stable isotope analysis can provide crucial insight into the function and development of early state‐level societies on the north coast of Peru. Materials and Methods Multi‐tissue (bone collagen, tooth enamel, hair, nail, skin, and tendon) stable isotope analyses (carbon, nitrogen, sulfur, and strontium) were conducted for 13 individuals from the lower Virú Valley. Results Non‐seasonal changes in a predominantly C4‐based terrestrial diet, with minimal inputs of marine foods were identified. One individual (Burial 5), however, had a stable isotope signature unlike any previously found on the north coast of Peru, indicating both a large contribution of C3‐terrestrial resources to their diet and an 87Sr/86Sr value suggestive of highland residence during childhood. Discussion This research provides the first strong stable isotope evidence of a highland individual within a coastal burial in northern Peru, new insight into the ritual killing event at Huaca Santa Clara during the late middle horizon and supporting evidence of the importance of C4 terrestrial resources to the developing Virú polity during the early intermediate period.
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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 | 0.001 |
| 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".