Freshwater Reservoir Offsets Investigated Through Paired Human-Faunal<sup>14</sup>C Dating and Stable Carbon and Nitrogen Isotope Analysis at Lake Baikal, Siberia
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Thirty-three paired accelerator mass spectrometry (AMS) radiocarbon dates on human and terrestrial faunal remains from the same Neolithic and Early Bronze Age graves are used to develop a correction for the freshwater reservoir effect (FRE) at Lake Baikal, Siberia. Excluding two outliers, stable nitrogen isotope (δ 15 N) values show a positive correlation (r 2 = 0.672, p < 0.000) with offsets in 14 C yr between paired human and fauna determinations. The highest offset observed in our data set is 622 yr, which is close to the value of ∼700 yr suggested for endemic seals in the lake. For each per mil increase in δ 15 N, the offset increases by 77 ± 10 yr in the overall data set. However, there are indications that different regression models apply in each of two microregions of Cis-Baikal. In the first, sites on the southwest shore of the lake and along the Angara River show a strong positive correlation between δ 15 N values and offsets in 14 C yr ( r 2 = 0.814, p < 0.000). In the other, the Little Sea, both δ 13 C and δ 15 N values make significant contributions to the model (adjusted r 2 = 0.878; δ 13 C p < 0.001; δ 15 N p < 0.000). This can be related to the complex 13 C ecology of the lake, which displays one of the widest ranges of δ 13 C values known for any natural ecosystem. The results will be important in terms of refining the culture-history of the region, as well as exploring the dynamic interactions of hunter-gatherer communities both synchronically and diachronically.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 it