The Effect of Cracks and Geo-Morphology on Evaporation from Clay Soils.
Bibliographic record
Abstract
Crack development in soils and the associated potential for higher evaporation rates are pertinent to many agricultural and engineering applications.Many researchers have attempted to model crack formation though none have succeeded to comprehensively capture it.Chertkov's model is a commonly cited theory for describing crack initiation and development.This theory uses only two independent parameters to model crack development, which makes it a promising tool for engineering applications.This research sought to verify Chertkov's model, as well as to analyze the coupled effect of crack growth and evaporation.A large scale (1.29 by 1.45 m by 0.09 m in thickness) clay drying test was carried out where crack growth, rate of evaporation and surface suction were monitored.Volume change and crack development were tracked using a 2-D laser scanner mounted on a scanning control mechanism, as well as by pixel analysis of surface photographs.A fractrographic analysis was also executed to determine the nature of soil deformation at crack tip.The drying test has shown that crack surfaces contributed at most to 6% of total evaporation before the onset of de-saturation and up to 63.4% after de-saturation.Results have also shown that Chertkov's model could successfully model crack growth, though the parameters had somewhat unrealistic values.While the fractographic analysis showed that some of Chertkov's model assumptions were violated, in particular that plastic strains appeared to be important, it is not clear whether these violations rule out this model as a useful tool.II
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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) | 0.002 | 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".