Moisture uptake and loss of GCLs subjected to thermal cycles from silty sand subgrade
Bibliographic record
Abstract
The effect on GCL hydration and dehydration, when subject to thermal cycles, of (1) GCL bentonite granularity (powdered vs. granular), (2) GCL geotextile type (scrim-reinforced nonwoven vs. woven), (3) subgrade macrostructure due to fines aggregation, and (4) subgrade density and fines content is examined. Results of 17 hydration tests were assessed for two virgin and deconstructed GCLs placed on a nominally silty sand subgrade at wfdn = 16% during daily thermal cycles when the airspace was heated to 60°C and cooled to 30°C. It is shown that bentonite granularity and mineralogy, the type of carrier geotextile and the subgrade conditions all significantly impact the GCL on cyclic hydration and that the moisture retention of a GCL is dependent on both the type of GCL and the properties of the underlying subgrade.
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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".