A KINETIC MODEL OF IMBIBITION IN SOILS
Bibliographic record
Abstract
A series of imbibition tests were conducted in soil samples that were contaminated or clean. The imbibition tests were done in a counter current fashion with controlled water rates, so that instant and complete saturation was explicitly avoided. Low-field NMR was used to monitor the imbibition process as a function of time. The spectra obtained were compared to “standard” spectra obtained with unconsolidated media. A number of unexpected and seemingly counter intuitive observations were made. It was found that the NMR spectra could be resolved into peaks that correspond to different pore sizes (as expected). However, the intensities and maxima of the peaks changed as a function of time, thus allowing for the monitoring of the redistribution of water in the porous media. Water ultimately migrated towards smaller pores from larger pores. As this migration occurred, the peaks corresponding to larger pores shrunk and the peaks corresponding to smaller pores increased. It is probable that substances in or on the surfaces of smaller pores develop as colloidal components or gels. It was possible to take these peaks and perform a kinetic analysis of water uptake in the porous medium. Kinetic data for wettable soils pointed to zero order kinetics for water uptake in the small pores. It was also found that soils previously contaminated and denoted as water-repellent appeared to follow second order kinetics for the water uptake in small pores. A kinetic model of imbibition can be formulated, with constants that describe the water uptake by different pore sizes. Furthermore, NMR offered an alternative for measurements of wettability in soils. This alternative is considered to be very important because there is no quantitative tool for measuring wetting properties of soils today. Qualitative measurement tests currently used are not theoretically sound.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".