Spatial and stratigraphic variation of near‐surface ground ice in discontinuous permafrost of the taiga shield
Bibliographic record
Abstract
Abstract The acceleration of permafrost thaw due to warming, wetting, and disturbance is altering circumpolar landscapes. The effect of thaw is largely determined by ground ice content in near‐surface permafrost, making the characterization and prediction of ground ice content critical. Here we evaluate the spatial and stratigraphic variation of near‐surface ground ice characteristics in the dominant forest types in the North Slave region near Yellowknife, Northwest Territories, Canada. Physical variation in the permafrost was assessed through cryostructure, soil properties, and volumetric ice content, and relationships between these parameters were determined. Near‐surface ground ice characteristics were contrasted between forest types. In black spruce forests the top of the permafrost was ice‐rich and characterized by lenticular and ataxitic cryostructures, indicating the presence of an intermediate layer. Most white spruce/birch forests showed similar patterns; however, an increase in the active layer thickness and permafrost thaw at some sites have eradicated the transition zone, and the large ice lenses encountered at depth reflect segregated ground ice developed during initial downward aggradation of permafrost. Our findings indicate that white spruce/birch terrain will be less sensitive than black spruce forests to near‐surface permafrost thaw. However, if permafrost thaws completely, white spruce/birch terrain will probably be transformed into wetland–thaw lake complexes due to high ground ice content at depth.
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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 | 0.000 | 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) | 0.001 | 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 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".