Modeling ground thermal conditions and the limit of permafrost within the nearshore zone of the Mackenzie Delta, Canada
Bibliographic record
Abstract
This study examines the interrelated effects of snow and ice on ground thermal conditions beneath regions of shallow water within the nearshore zone of the Mackenzie Delta. Field‐ and model‐based data were used to determine the thermal boundary conditions at the sediment bed surface and to define the contemporary limit of permafrost. Over two consecutive winters, mean sediment bed temperatures deviated up to 9.8°C beneath bottom‐fast ice that ranged from 10 cm to 100 cm thick, with intrasite variability as much as 4.7°C. Measured and modeled temperatures were found to exponentially relate to the duration of time ice is bottom‐fast with the sediment bed. Mean winter ground temperatures at this boundary were predicted within ±0.25°C of the observed measurements using numerical thermal modeling. As on‐ice snow depth decreased, the limit of equilibrium permafrost shifted toward progressively deeper water because of longer durations of ice contact and greater heat loss from the ground. The critical water depth for permafrost under equilibrium conditions was 84 cm (calculated from an ice thickness of 93 cm), which is equivalent to an ice contact time of 142 days. Equilibrium permafrost was mapped beneath 393.8 km2 of bottom‐fast ice. An additional 387.9 km2 exhibited seasonal ground freezing in the winter of 2006–2007. Areas affected by bottom‐fast ice represent locations that are actively receiving sediment from distributary channels. These results provide the first estimates of contemporary permafrost distribution for shallow water regions of the outer Mackenzie Delta.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".