Effect of soil properties and soil disturbance on frost heaving of mineral soil: a laboratory experiment
Bibliographic record
Abstract
A laboratory experiment was done to identify the properties that make a substrate susceptible to frost heaving. Tests were carried out on nondisturbed soil cores (fresh and dry) of Ae and B horizons from sand, loamy sand, and sandy loam in a freezing cabinet (–3.5 °C). Cores were continuously supplied with water from below. Freezing tests were repeated after soil disturbance (V-shaped furrow, 50% increase in surface area). The effects of texture, horizon, drying, and disturbance on frost heaving were tested using repeated-measures analysis of variance with soil elements (organic Al, organic Fe, inorganic Al, inorganic Fe, C, and N) and soil fractions (clay, fine silt, coarse silt, fine sand, and coarse sand) as covariates. The effect of horizon was as important as that of texture, and soil disturbance increased frost heaving. Disturbed fresh B horizon from loamy sand and sandy loam heaved the most (soil expansion >5% in height), whereas nondisturbed dry Ae horizon, regardless of texture, and nondisturbed dry B horizon from sand heaved the least (soil expansion <0.8% in height). Soil elements and fractions had an impact on frost heaving, especially organic Al, although it was of a smaller magnitude. Therefore, it is suggested that seedbeds or planting substrates be prepared by exposing the nondisturbed Ae horizon only, that is, without exposing or disturbing the B horizon.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".