The influence of freeze–thaw cycles on the mechanical properties of paleosols: based on a multiscale research
Bibliographic record
Abstract
To investigate the multiscale effects of freeze–thaw cycles on the mechanical properties and structural damage of paleosols, remodeled paleosol specimens at natural moisture content were subjected to multiple freeze–thaw cycles, followed by scanning electron microscopy, nuclear magnetic resonance (NMR) pore testing, and triaxial shear testing, and then the shear strength deterioration mechanism of paleosols was elaborated on from three aspects: fine, mesoscopic, and macroscopic. The main experimental results were as follows: (1) at the fine level, the NMR T2 spectrum distribution curve showed one primary and two secondary peaks, in which the main spectrum occupied the majority, and the spectrum area showed an exponential function distribution relationship with the number of freeze–thaw cycles. With the accumulation of freeze–thaw cycles, the medium and large pores increased significantly. (2) At the mesoscopic level, when the specimens underwent freeze–thaw cycles, the interparticle contact pattern and particle morphology changed and the particle roundness increased. As the freeze–thaw cycle continued, fissures gradually developed and increased the most after the first freeze–thaw cycle, but the probability entropy of soil particles showed a decreasing trend with the increase of the number of freez–thaw cycles. (3) At the macro level, the number of freeze–thaw cycles gradually accumulated, the specimen stress–strain curve softened significantly, the shear strength deterioration effect was obvious, the deterioration value was the largest after one freeze–thaw cycle and gradually stabilized after 10 cycles, and the deterioration effect of cohesion was greater than that of the internal friction angle.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".