Correlation and interpretation of paleosols and loess across European Russia and Asia over the last interglacial–glacial cycle
Bibliographic record
Abstract
Abstract Loess-paleosol sequences of the last interglacial-glacial cycle are correlated from European Russia to central Siberia and the Chinese Loess Plateau. During cold periods represented by marine oxygen isotope stages (OIS) 2 and 4, loess deposition dominated in the Russian Plain and the Loess Plateau. In central Siberia, loess deposition took place also, but five to seven thin, weakly developed paleosols are identified in both stages. OIS 3, in the Chinese Loess Plateau near Yangchang, consists of a loess bed that is flanked by two weakly developed paleosols. At Kurtak, Siberia, OIS 3 is represented by two distinct, stacked paleosols with no loess bed separating the paleosols. In the Russian Plain, OIS 3 consists of a single, possibly welded paleosol, representing upper and lower stage-3 climates. Brunisols and Chernozems dominate the profiles in China and Siberia, whereas Regosols, Luvisols, and Chernozems are evident in the northern and southern Russian Plain, respectively. OIS 5 is represented in China and the Russian Plain by pedo complexes in a series of welded soils, whereas in contrast, the Kurtak site consists of six paleosols with interbedded loess. The paleosols consist largely of Brunisols and Chernozems. Although the three areas examined have different climates, geographical settings, and loess source areas, they all had similar climate changes during the last interglacial-glacial cycle.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".