Lateglacial and Holocene chronology of climate‐driven postglacial landscape evolution in northeast Greenland
Bibliographic record
Abstract
The Greenland Ice Sheet is highly sensitive to climate change, leading to significant retreat along its edges. This rapid ice loss contributes to rising sea levels and impacts the Earth's climate stability. Understanding the extent of recent glacier retreat is crucial in order to determine if it is unprecedented or within ranges of natural variability. Palaeoenvironmental studies aim to identify past glacial phases and landscape changes using advanced dating methods such as cosmic ray exposure (CRE) dating. In NE Greenland, CRE dating has helped establish the timing of glacial oscillations, yet a comprehensive understanding of glacial fluctuations during specific periods still needs to be developed. This study aims to chronologically constrain the postglacial landscape evolution of two NE Greenland valleys from the Young Sund–Tyrolerfjord area (74°N, 20–25°E) from the onset of deglaciation and throughout the Holocene to better understand glacial and postglacial changes. The chronological framework relies on 27 10 Be cosmic‐ray exposure ages that constrain our interpretation of the geomorphological features in both valleys. Inconsistencies were observed in the ages dataset, highlighting potential bias associated with nuclide inheritance and post‐glacial dynamics. Despite limitations, the CRE results confirm the general pattern observed in NE Greenland: (i) major deglaciation and disconnection of glaciers from the main glacial systems during the Lateglacial and Early Holocene with a rapid but not homogeneous deglaciation within the range from ~14.3 to 11.9 ka; (ii) no evidence of glacial activity during the Middle Holocene, probably associated with the withdrawn position of the ice masses’ fronts; and (iii) glacier expansion during the Late Holocene, with a Little Ice Age advance as the last significant period of glacial regrowth.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".