Evolution of high-Arctic glacial landforms during deglaciation
Bibliographic record
Abstract
Glacial landsystems in the high-Arctic have been reported to undergo geomorphological transformation during deglaciation. This research evaluates moraine evolution over a decadal timescale at Midtre Lovénbreen, Svalbard. This work is of interest because glacial landforms developed in Svalbard have been used as an analogue for landforms developed during Pleistocene mid-latitude glaciation. Ground penetrating radar was used to investigate the subsurface characteristics of moraines. To determine surface change, a LiDAR topographic data set (obtained 2003) and a UAV-derived (obtained 2014) digital surface model processed using structure-from-motion (SfM) are also compared. Evaluation of these data sets together enables subsurface character and landform response to climatic amelioration to be linked. Ground penetrating radar evidence shows that the moraine substrate at Midtre Lovénbreen includes ice-rich (radar velocities of 0.17 m ns −1 ) and debris-rich (radar velocities of 0.1–0.13 m ns −1 ) zones. The ice-rich zones are demonstrated to exhibit relatively high rates of surface change (mean thresholded rate of −4.39 m over the 11-year observation period). However, the debris-rich zones show a relatively low rate of surface change (mean thresholded rate of −0.98 m over the 11-year observation period), and the morphology of the debris-rich landforms appear stable over the observation period. A complex response of proglacial landforms to climatic warming is shown to occur within and between glacier forelands as indicated by spatially variable surface lowering rates. Landform response is controlled by the ice-debris balance of the moraine substrate, along with the topographic context (such as the influence of meltwater). Site-specific characteristics such as surface debris thickness and glaciofluvial drainage are, therefore, argued to be a highly important control on surface evolution in ice-cored terrain, resulting in a diverse response of high-Arctic glacial landsystems to climatic amelioration. These results highlight that care is needed when assessing the long-term preservation potential of contemporary landforms at high-Arctic glaciers. A better understanding of ice-cored terrain facilitates the development of appropriate age and climatic interpretations that can be obtained from palaeo ice-marginal landsystems.
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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 | 0.001 | 0.000 |
| 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".