Establishment and experiment of a pressure-bearing subsidence model of layered soil in forest region
Bibliographic record
Abstract
Forest vehicle operation causes different degrees of compaction damage to the soil, which is related to the pressure-bearing characteristics of the soil. However, scholars have not profoundly investigated the pressure-bearing factors of forest soil. In this paper, disturbed brown coniferous forest soil was collected layer by layer, dried, screened, and tested with indoor pressing-plate tests with different pressing-plate shapes and diameters (side lengths). A kind of pressure–subsidence ( P–Z) curve of hard soil, which is different from those of farmland soil and homogeneous remolded soil, was obtained and drawn as the P–Z curve. The results show that in the process of pressure subsidence, the forest soil gradually changed from loose to compact. Furthermore, the change of pressure-bearing subsidence of layered soil from this forest region was characterized first by the rapid increase of soil subsidence with the increase of pressure. Then, the subsidence speed became slower with the increase of pressure; finally, subsidence speed was much less affected by the increase in pressure. According to the pressure-bearing subsidence curve of forest soil, a new subsidence model is put forward in this paper. The new model has a good prediction effect on the subsidence curve of forest soil. This paper aims to provide a theoretical basis for studying soil pressure-bearing characteristics and the development of vehicles in high-passing forest areas.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".