Geomorphology of Gullies at Thomas Lee Inlet, Devon Island, Canadian High Arctic
Bibliographic record
Abstract
Abstract Slopes in and around Thomas Lee Inlet (Devon Island, Nunavut, Canada) are eroded by means of gullying, yet the driving factors, such as the nature of the substrate and availability of different sources for water, influencing gully morphology remain poorly understood. Here we investigate the factors that contribute to gully formation using a combination of satellite mapping, field observations and statistical analysis of morphological data. In total, 161 gullies were mapped within the 126 km2 study area. Factors linked to gullies, such as the nature of its substrate and the presence of glaciers, were integrated into a spatial geodatabase. A Factor Analysis of Mixed Data performed on the geodatabase was used to discriminate which factors may influence gully geometry. Our results show that the type of geological formation has a strong impact on gully slope. In addition, supplemental sources of water are often found near alcoves of the steep, longer and mature gullies, and levees often form in their aprons. Immature debris flow‐like gullies were dryer and found on short and variable (from steep to gentle) slopes. This detailed study of the rocky and arid Thomas Lee Inlet plateaus and slopes provides the first insight into gullied slopes as a hydrological component connecting upland units to downslope in this area.
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 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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| 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".