Freshwater Reservoir Effect on Redating of Eurasian Steppe Cultures: First Results for Eneolithic and Early Bronze Age Northeast Kazakhstan
Bibliographic record
Abstract
Freshwater reservoir effects (FRE) can cause problems when radiocarbon dating human skeletal material from the Eurasian steppe. This article presents the first results of research into the extent of the FRE in the sites of Borly 4 (Eneolithic) and Shauke 1 and 8b (Early Bronze Age), northeastern Kazakhstan. Accelerator mass spectrometry (AMS)14C dating and stable isotope (δ13C, δ15N) analysis of associated groups of samples (32 samples, 11 groups in total) demonstrate the following: (a) the diet of the humans and fauna analyzed was based on the C3foodchain with no evidence of a C4plant (such as millet) contribution; aquatic resources apparently were a continuous dietary feature for the humans; (b) the first14C dates obtained for the Upper and Middle Irtysh River region attribute the Eneolithic period of the area to the 34th to 30th centuries BC, and the Early Bronze Age to the 25th to 20th centuries BC, with a ~450-yr hiatus between the two periods; (c) the maximum fish-herbivore freshwater reservoir offset observed equals 301 ± 4714C yr. As such,14C dates from aquatic and human samples from the area need to be interpreted with caution as they are likely to be affected by the offset (i.e. appear older). The article also discusses the effect of a sodium hydroxide (NaOH) wash on δ13C, δ15N, C:Natomiclevels and collagen yields of the bone samples. Our results indicate a minor but significant effect of NaOH treatment only on C:Natomicratios of the samples.
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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 | 0.001 | 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".