Landsystems of Morsárjökull, Skaftafellsjökull and Svínafellsjökull, outlet glaciers of the Vatnajökull Ice Cap, Iceland
Bibliographic record
Abstract
This study utilizes a landsystem approach to analyse the landforms and sediments exposed on the forefields of three closely spaced outlet glaciers of the Vatnajökull Ice Cap, southeast Iceland; Morsárjökull, Skaftafellsjökull and Svínafellsjökull, in order to determine how individual glacier and environmental characteristics influence landscape development. Analysis of satellite imagery and fieldwork were used in conjunction to examine the geomorphology and sedimentology of the forefields, and to define the characteristic landsystems of each of the glaciers. Morsárjökull and Skaftafellsjökull have similar proglacial fields, with similarities in the distribution and scale of the landforms, and their characteristics conform to the established active temperate landsystem. Svínafellsjökull differs significantly from the other glaciers having a proglacial field that more closely resembles an early stage debris‐charged landsystem. Variations between the glaciers in terms of their ice distribution (hypsometry, equilibrium line altitude), bedrock type, topography and debris content are important factors that contribute to the landsystem variability evident in their proglacial fields. The forefields of these three glaciers may be used as analogues to enhance understanding of palaeoenvironmental conditions that existed along the southern margin of Pleistocene glaciers that covered much of northern North America and Europe in the past.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".