Multi-methodological three-dimensional investigation of a closed-system Pingo in Northwestern Canada
Bibliographic record
Abstract
The Mackenzie-Delta region is known for widespread permafrost and the association of different landforms, which are characteristic of a periglacial landscape development. Especially the density of closed-system pingos is nowhere on earth higher than in the area of the Tuktoyaktuk Peninsula. This type of pingos is common only in the continuous permafrost zone and is very sensitive to changing thermal conditions. In this study, we investigated the surface and subsurface conditions in the area of such a closed-system Pingo near Parsons Lake in the southern part of the Tuktoyaktuk Peninsula to study its internal structure and evolutional state. Therefore, we used a combined approach of electrical resistivity tomography (ERT), ground-penetrating radar (GPR) and manual frost probing. In addition, a high-resolution digital elevation model and an orthophoto were generated using in situ drone acquisitions. These enabled a detailed and areawide mapping of surface characteristics (e.g. vegetation height or type) and should contribute to the investigation of linkages between surface and subsurface characteristics. Such a linkage could be observed comparing the mapped vegetation type and heights with active layer depths derived from manual frost probing and GPR measurements. Both parameters show a significant zonation in the area of the pingo and its surrounding. In addition, the results of the quasi three-dimensional ERT measurements could deliver new insights into the three-dimensional internal structure of the pingo and a massive ice core could be detected. However, the shape as well as the position of the massive ice core in relation to the elevated surface of the pingo differ from the previous theory of closed-system pingo formation and therefore raises some questions. Also the existence of a talik could be confirmed, but its position beside the ice core within the eastern flank of the pingo and not below the massive ice core also differs from the theoretical models and should be discussed.
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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 | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".