Influence of Initial Saturation Level on Collapsibility of Polymer-Treated Gypsum Soils
Bibliographic record
Abstract
During the current study, several single odometer tests were executed to explore the exert an influence of initial saturation levels on the collapsibility of both natural and polymertreated gypseous soil.Two gypseous soils with different gypsum concentrations (18 and 58%) were taken from various locations within the Salah-Al-Deen government in Iraq.Many studies have examined the influence of polymer content on the shear strength, collapsibility, and permeability of gypseous soil.This study aims to ascertain how polymer-treated compacted gypseous soils at field dry unit weight are influenced by the initial saturation ratio considering their collapsibility.Soils were compacted with different initial water content to specify different initial saturation levels from 20 to 90% for each case.Polymer was added to soils with three percent (3, 6, and 9%).The stabilizer concentration of the polymer was previously diluted in water added to the soil mixture.Depending on the moisture content, the dilution ratio was specified to achieve a certain saturation degree and the amount of stabilizer used.The results show that the collapse index sharply dropped as the beginning saturation ratio increased.The optimum initial saturation level that achieves minimum collapse index is 50% for natural and polymertreated soil.The optimum polymer content that achieved the minimum collapse index was 3%.The soil was compacted at an initial saturation level of 50% and polymer content of 3%, decreasing the collapse index for soil with gypsum content of 18% and 58% by 92% and 89%, respectively.A theoretical equation (which yielded an R2 value of 0.925) was predicted to calculate the potential collapse index of natural and polymer-treated gypseous soils that incorporates all the coefficients studied during this research.
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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 | 0.000 |
| 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".