Using δ<sup>2</sup>H in Human Bone Collagen to Correct for Freshwater <sup>14</sup>C Reservoir Offsets: A Pilot Study from Shamanka II, Lake Baikal, Southern Siberia
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Bibliographic record
Abstract
ABSTRACT There is increasing awareness of the need to correct for freshwater as well as marine reservoir effects when undertaking radiocarbon ( 14 C) dating of human remains. Here, we explore the use of stable hydrogen isotopes (δ 2 H), alongside the more commonly used stable carbon (δ 13 C) and nitrogen isotopes (δ 15 N), for correcting 14 C freshwater reservoir offsets in 10 paired human-faunal dates from graves at the prehistoric cemetery of Shamanka II, Lake Baikal, southern Siberia. Excluding one individual showing no offset, the average human-faunal offset was 515±175 14 C yr. Linear regression models demonstrate a strong positive correlation between δ 15 N and δ 2 H ratios, supporting the use of δ 2 H as a proxy for trophic level. Both isotopes show moderate but significant correlations ( r 2 ~ 0.45, p < 0.05) with 14 C offsets (while δ 13 C on its own does not), though δ 2 H performs marginally better. A regression model using all three stable isotopes to predict 14 C offsets accounts for approximately 65% of the variation in the latter ( r 2 =0.651, p =0.025), with both δ 13 C and δ 2 H, but not δ 15 N, contributing significantly. The results suggest that δ 2 H may be a useful proxy for freshwater reservoir corrections, though further work is needed.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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 it