Identifying ice lens initiation of frozen soils using particle image velocimetry method
Bibliographic record
Abstract
Frost heave occurring in embankments seriously threatens the safe operation of transportation infrastructures in cold regions. When and where the ice lens initiates are key to understanding the mechanism of frost heave in soils. This study develops a novel particle image velocimetry technology specifically suited for a frost heave apparatus. The displacement, velocity, and strain of the three-dimensional frost heave surface are acquired with this technology, and the monitoring accuracy reaches the micron level. A series of one-dimensional freezing tests are carried out for silt soil to validate the applicability of this novel technology. The validation of the test results confirms the effectiveness of the method. The results indicate that the measured displacement and velocity induced by the initiation of ice lenses can clearly depict the development of the frost heave process. Ice lens initiation can be identified where peaks of strain values occur during the freezing stage. The proposed criterion, based on image velocimetry measurements, thus provides a new tool for assessing the formation of ice lenses during frost heave process.
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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 | 0.001 | 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".