Long‐Term, High‐Resolution Permafrost Monitoring Reveals Coupled Energy Balance and Hydrogeologic Controls on Talik Dynamics Near Umiujaq (Nunavik, Québec, Canada)
Bibliographic record
Abstract
Abstract Rising temperatures in the Arctic and subarctic are driving the rapid thaw of permafrost by reducing permafrost cooling, increasing active layer thickness, and promoting talik formation. In this study, the cyrohydrogeology of a permafrost mound located within the discontinuous permafrost zone near Umiujaq (Nunavik, Québec, Canada) is characterized through the analysis of a dataset covering more than two decades of monitoring. This dataset captures a high degree of interannual variability in air temperature and ground thermal conditions, as well as the dynamics of a supra‐permafrost talik. Data indicate that variable saturation and advective heat transport directly contribute to the expansion and contraction of the talik. Data further indicate the presence of two distinct thermo‐hydrologic settings resulting from differences in surface conditions, as well as subsurface thermal and flow regimes. The first, found at the top of the mound feature, is characterized by very low moisture contents (<0.05 m3/m3), while the second, found at the side of the mound feature, shows higher annual moisture contents that strongly influence the dynamics of heat and groundwater flow. The data were synthesized into a detailed conceptual model of the cyrohydrogeological dynamics that highlights the important role of hydrogeological characterization and long‐term data sets in understanding the effects of groundwater flow on seasonal frost and permafrost dynamics. Specifically, the results presented here show that in the absence of long‐term data sets, longer‐period transient phenomena such as talik expansion and contraction may be misrepresented as uni‐directional feedback loops, as opposed to highly dynamic temporary phenomena.
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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 | 0.001 | 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".