Exploring Soil–Water Characteristic Curves in Transitional Oil Sands Tailings
Bibliographic record
Abstract
Soil–water characteristics curves (SWCC) have proved useful in estimating parameters used in modeling unsaturated geotechnical properties of soils including permeability and strength. Either saturation, gravimetric, and instantaneous and initial volumetric water content designation can be used to develop SWCCs. Studies have shown that any of the designations will give good estimates for soils that do not undergo volume change with suction change whereas, for soils that undergo substantial volume change, only saturation and instantaneous volumetric water content designation obtained by incorporating shrinkage curves can give correct estimates. Transition oil sands tailings have fines content that cannot be categorized as sandy or fine materials, and research on volume change with suction change in these materials is limited. In this study, HyProps, Tempe cells, and a chilled-mirror water potential meter were used to measure suction and corresponding water contents for samples that were prepared by mixing coarse sand and Fluid Tailing by ratios that mimic transition zone tailings. Shrinkage tests were also performed to observe the extent of volume change with suction increase. Air Entry Values (AEV) estimated from SWCCs based on gravimetric water content were found to be lower than those estimated from saturation-based SWCCs due to substantial volume changes in these materials with suction increase. The use of saturation water content designation is recommended in estimating AEV for transitional oil sands tailings. This is useful information in predicting the long term unsaturated geotechnical behavior of these materials for environmental management and safety purposes.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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".