Diet Transition or Human Migration in the Chinese Neolithic? Dietary and Migration Evidence from the Stable Isotope Analysis of Humans and Animals from the Qinglongquan Site, China
Bibliographic record
Abstract
Abstract The Qinglongquan site, China, includes materials from the Neolithic Qujialing (3000–2600 bc) and Shijiahe (2600–2200 bc) periods, and lies within the Sui‐Zao Corridor that connects the Nanyang Basin in the north and the Hanjiang River Plain in the south. Previous research suggested a dietary shift from rice‐based to millet‐based agriculture between the Qujialing and Shijiehe periods at this site. The reason for this dietary shift is still unclear, and it is possible because of immigration into the region by people who already had a mainly C4‐millet‐based diet (i.e. from Northern China). In this study, we examine the carbon (δ13C) and nitrogen (δ15N) results and present sulfur (δ34S) isotope analyses of human (n = 27) and animal (n = 36) samples to test the hypothesis of whether this dietary shift was due to migration. The δ34S values of the Qujialing humans ranged from 5.5‰ to 8.1‰ [average 6.5‰ ± 1.0 (n = 7)], and the δ34S values of the Shijiahe humans ranged from 4.1‰ to 7.4‰ [average 5.8‰ ± 0.9 (n = 18)]. Because these values overlapped and were similar to the animal δ34S results [4.3‰ to 8.8‰, average of 6.6 ± 1.3‰ (n = 31)], no evidence of migration was found for the humans with the different diets at the Qinglongquan site. Copyright © 2015 John Wiley & Sons, Ltd.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".