Modelling near-surface ice content and midwinter melt events in mineral soils
Bibliographic record
Abstract
Over winter freeze–thaw events are notoriously difficult to represent in hydrologic models and have serious implications for the hydrologic function of intermittently freezing regions. Changing climate is leading to more frequent mid-winter thaw events. Midwinter thaw events are often the cause of flooding due to the combined impacts of snowmelt, precipitation, and limited soil infiltrability. A numerically efficient, semi-analytical coupled thermal and mass transport model is presented that represents the ice content of near-surface soil, and reports the depth of freezing/thawing. The model tracks pore ice formation and mean soil temperature in terms of enthalpy. It is tested against data collected in Southern Saskatchewan and is shown to capably reproduce field observations of frozen, thawed or transitioning soils. This numerically efficient model can be incorporated into regional hydrologic models where it is expected to improve predictions of soil ice content, leading to improved estimates of over-winter streamflow and flood potential.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".