Cryogenic wedges and cryoturbations on the Ordos Plateau in North China since 50 ka BP and their paleoenvironmental implications
Bibliographic record
Abstract
Abstract During the last 50 ka, cryogenic wedges on the Ordos Plateau formed during three major periods: (i) early local Last Glaciation, ca. 50 ka BP; (iii) local Last Permafrost Maximum(local LPM), 25–19 ka BP; and (v) post‐local LPM, 16–9 ka BP. Cryoturbations mainly formed in the following periods: (ii) pre‐local LPM, 45–30 ka BP and (iv) ~ 20 ka BP. The coldest periods with well‐developed permafrost (i and iii) were most conducive for forming cryogenic wedges. The following periods of warming climate and degrading permafrost favored the formation of cryoturbations. During the local LPM, sand wedges and polygons were well developed and widely distributed on the Ordos Plateau when mean annual air temperatures (MAATs) were approximately 12°C lower than that at present. At ~30 ka BP, MAAT was 6–7°C lower than that at present. Paleoclimate conditions on the Ordos Plateau were reconstructed since 50 ka BP as follows: cold (ca. 50 ka BP) → cool (45–30 ka BP) → very cold (25–19 ka BP) → cool (19–9 ka BP) → intermittent warming until the present day. The amount of precipitation fluctuated, but with a general trend of drying since 50 ka BP. Under the next generally warming climate (after 9 ka BP), permafrost gradually degraded and eventually disappeared from the Ordos Plateau.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".