Low- and high-frequency climate variability in eastern Beringia during the past 25 000 yearsThis article is one of a series of papers published in this Special Issue on the theme <i>Polar Climate Stability Network</i>.
Bibliographic record
Abstract
We present new temperature and precipitation reconstructions for the past 25 000 cal. years BP from across eastern Beringia based on a network of pollen diagrams, an updated modern pollen calibration database, and an improved methodology using the modern analogue technique (MAT). Time series show July temperatures were around 4 °C lower during full glacial and January temperatures were about 2 °C lower than present. Annual temperatures rose beginning around 16 000 cal. years BP, reaching a maximum around 12 000 cal. year BP. The warming was more rapid in southern Beringia. Annual precipitation varied by 250 mm during the past 25 000 cal. years BP. Maps of reconstructed precipitation patterns show increasingly drier conditions since 12 000 cal. years BP. that vary regionally, suggesting Holocene atmospheric circulation changes at multiple time and space scales. Orbitally forced seasonality changes during the late glacial and early Holocene resulted in reversed seasonal temperature reconstructions due to methodological constraints using the MAT and (or) non-analogue conditions. The magnitude of millennial-scale climate variability in this region was greater during the last glacial and late glacial periods than during the past 8000 years.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".