Lithalsa distribution, morphology and landscape associations in the Great Slave Lowlands, Northwest Territories
Bibliographic record
Abstract
The distribution of ice-rich terrain is an important geotechnical consideration for the engineering of northern infrastructure. Lithalsas represent one form of ice-rich terrain that can be identified on the basis of surface geomorphology and cryostratigraphy. A total of 1,777 ice-rich lithalsas were mapped over 3,680 km2 using monochromatic stereo-pair airphotos, across the Great Slave Lowlands and Uplands, NWT, Canada. Boreholes indicate lithalsas in this region consist of ice-rich silt and clay, with segregated ice lenses up to 10 cm thick. Three distinct morphologies are recognized from LiDAR bare-earth DEMs including; (i) circular, (ii) linear and (iii) crescentic plan-view shapes, which exhibit hill-like or ridge-like forms up to 8 m in height and more than 100 m in width. The linear relationship between lithalsa height and width indicates that 1 cm of vertical growth may be accompanied by 15 cm of lateral growth at the peripheral edges. Lithalsa distribution is skewed towards lower elevations, with 97.7% located within the Great Slave Lowlands. These features predominately occur adjacent to water bodies and follow the regional distribution of frost susceptible glaciolacustrine silt and clay. Landscape associations suggest lithalsa formation is controlled by sedimentological, thermal and hydrological conditions. This Open File reports the first account of lithalsas within this region.
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 | 0.001 | 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".