The Compound Impacts of Changing Temperature and Snow Cover on Freeze and Thaw Patterns across Québec
Bibliographic record
Abstract
Seasonal Freeze-Thaw cycles (FT) is a key to environmental processes and socioeconomic activities across northern latitudes. The large-scale dynamics of FT are mainly governed by air temperature and snow depth. We argue that this physical control can be empirically characterized, represented, and simulated by the trivariate dependence structure between FT, temperature, and snow depth. To showcase this, we consider the gridded data of these variables over Québec, Canada, and use canonical vine copulas to formulate the trivariate interdependence between FT, temperature, and snow depth in different grids and ecozones. Our results reveal different dependence structures across Québec ecozones, pointing at the role of landscape in regulating the impacts of snow depth and temperature on FT. Having the trivariate dependence, we use a bottom-up impact assessment approach to address the alterations in FT characteristics under single and compound changes in the temperature and snow depth.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".