Coupled model on consolidation and porewater mobilization within low-permeability sediments
Bibliographic record
Abstract
Groundwater, a crucial freshwater resource, constitutes over 95% of the world's discovered freshwater. It effectively mitigates the uneven spatial distribution of surface water, prompting the development of industry, agriculture, and human society. In most cases, the exploitation of groundwater resources inevitably involves the consolidation of low-permeability sediments. The mobilization of porewater from it, carrying various chemical components, had leaded to worldwide water quality degradation and endemic diseases. Consequently, close attention and control over the mobilization of porewater from low-permeability sediments during extraction is urgently needed. However, the mobilization of porewater caused by consolidation is often confused with porous medium flow. Existing models considering porewater mobilization during compaction contain incomplete assumptions about porewater flow and solute mobilization within low-permeability sediments, making it challenging to incorporate porewater mobilization from these sediments into reactive solute transport models during groundwater abstraction. Further investigation would benefit grasping water quality evolution during groundwater abstraction and for risk management of clean freshwater resources. In this study, we developed a physical device to simultaneously monitor the consolidation and porewater mobilization in low-permeability sediments. By refining Gibson's large deformation consolidation theory based on experimental observations, we describe both consolidation and porewater mobilization processes within low-permeability sediments under a unified framework. This approach aims to provide new insights and feasible solutions for integrating low-permeability sediments into the watershed-scale three-dimensional groundwater model, particularly for understanding water quality origins in Quaternary aquifers.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".