Recent advances in paleoclimatological studies of Arctic wedge‐ and pore‐ice stable‐water isotope records
Bibliographic record
Abstract
Abstract Late Pleistocene and Holocene ground ice are common throughout the Arctic. Some forms of relict ground ice preserve local meteoric water, and their stable oxygen‐ and hydrogen‐isotope ratios can be used to reconstruct past air temperatures. In this paper, we review the formation and sampling of two forms of relict ground ice—wedge ice and pore ice—and recent (2010–2019) advances in paleoclimatological studies of ground‐ice stable isotope records in the Arctic. Recent advances are attributed to better chronological constraints and refined understandings of the systematics and seasonality of relict wedge ice and pore ice. A rich network of ice‐wedge records has emerged, primarily from the Siberian Arctic, whereas pore‐ice records are less common. The ice‐wedge network depicts a robust pattern of late Pleistocene cooling, and remarkably similar temperature depressions during Marine Isotope Stages 3 and 2. Very high‐resolution wedge‐ and pore‐ice stable isotope chronologies have been established recently and used to reconstruct winter and summer climate histories and to assess seasonal dependencies in insolation‐forced climate. Reports of ancient (>125 ka BP) ground ice demonstrate its long‐term persistence, and its potential to expand our knowledge of Quaternary climate dynamics in the terrestrial Arctic.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".