Physicochemical deterioration mechanism of red-bed mudstone during water–rock interactions: insights from soaking experiments
Bibliographic record
Abstract
The softening of red-bed mudstone upon water exposure is a critical factor triggering geological hazards such as landslides. Previous studies have not sufficiently clarified the physicochemical mechanisms underlying the deterioration of red-bed mudstone under water–rock interactions. This paper takes the red-bed mudstone from three landslides in Qinghai. Through soaking experiments and combined with X-ray diffraction, scanning electron microscopy, pore and crack analysis system, ion chromatography, and inductively coupled plasma optical emission spectrometer, the changes in mineral composition, pore structure, and solution ion concentration of the mudstone before and after the soaking were tested and analyzed. Results indicate that the degradation of red-bed mudstone under water–rock interactions is the outcome of the combination of mineral dissolution and secondary formation, clay mineral expansion, water–rock ion exchange, and hydraulic erosion. Hydrolysis of clay minerals, hydrolysis and carbonation of feldspar and calcite, increased porosity by 52%–172.6% and pore quantity by 63.1%–197.9%. The cations released from the hydrolysis of feldspar and calcite participated in clay mineral transformation, increasing total clay minerals content by 3.95%–7.88%. These chemical reactions are key drivers of the deterioration of microstructure. Additionally, the increase in clay minerals and their expansion further degrade the mechanical properties of mudstone.
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| 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".