Guidelines for cold‐regions groundwater numerical modeling
Bibliographic record
Abstract
Abstract The impacts of ongoing climate warming on cold‐regions hydrogeology and groundwater resources have created a need to develop groundwater models adapted to these environments. Although permafrost is considered relatively impermeable to groundwater flow, permafrost thaw may result in potential increases in surface water infiltration, groundwater recharge, and hydrogeologic connectivity that can impact northern water resources. To account for these feedbacks, groundwater models that include the dynamic effects of freezing and thawing on ground properties and thermal regimes have been recently developed. However, these models are more complex than traditional hydrogeology numerical models due to the inclusion of nonlinear freeze–thaw processes and complex thermal boundary conditions. As such, their use to date has been limited to a small community of modeling experts. This article aims to provide guidelines and tips on cold‐regions groundwater modeling for those with previous modeling experience. This article is categorized under: Engineering Water > Methods Science of Water > Hydrological Processes
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 | 0.009 | 0.033 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.007 | 0.004 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.031 | 0.036 |
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".