Water retention curve and hydraulic conductivity function of highly compressible materials
Bibliographic record
Abstract
A model capable of describing the suction-induced consolidation curve (void ratio function) and water retention curve (WRC) of highly compressible materials (HCM) is developed, validated, and finally applied to describe the WRC of deinking by-products (DBP). DBP are a highly compressible by-product of paper recycling used in geoenvironmental applications. Validation is conducted by modelling the WRC and the void ratio function for a well documented silty sand from Saskatchewan, Canada. The WRC and void ratio function were used to predict its hydraulic conductivity function (k-function). The water content, suction, and volumetric deformation data of DBP are obtained using an experimental technique that allows determination of the WRCs of HCMs that is suitable for prediction of the DBP k-function. The results show that volumetric water contents are underestimated if volume changes are not accounted for, leading to inaccuracies in the WRCs, thus inaccurately predicted k-functions. It is shown that the newly developed model is better suited for HCMs than currently available models, in particular for HCMs that continue to undergo significant volume changes when the applied suction exceeds the air-entry value.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".