The Cold Vadose Zone: Hydrological and Ecological Significance of Frozen‐Soil Processes
Bibliographic record
Abstract
Approximately 50% of soils in the Northern Hemisphere experience seasonal freezing and thawing, which influences physical, chemical, and biological processes in the vadose zone. Soil freeze–thaw drives mechanical processes, including frost heave and soil aggregate formation and breakdown, and controls snowmelt infiltration and runoff. These hydrologic processes determine the soil moisture conditions, which affect plant mortality and growth, soil microbial activities, and nutrient (e.g., C and N) cycles. Nutrients leached from the thawed soil, often with rapid infiltration of snowmelt water, may affect the quality of the groundwater and surface water, in combination with enhanced erosion and sediment load due to freeze–thaw. Nutrients released as greenhouse gases may contribute to climate feedback. With recent climate warming and changes in the extent and depth of frozen soil and permafrost, it is important to understand frozen‐soil processes and their interaction with the environment. The objective of this review is to highlight important aspects of soil freeze–thaw and related processes and to point out research challenges and opportunities in the cold vadose zone.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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 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".