Bibliographic record
Abstract
S loosening is a very important performance indicator forsub-soiling tools. In this study, soil loosening effects from a ripper (a sub-soiling tool) was investigated through numerical modeling. To assist the model development, tests of the ripper were performed in a field with a clay soil texture. In the tests, the ripper was operated at a tillage depth of 300 mm and travel speed of 3 km/h. Before testing, soil cone indices of the undisturbed field were measured using a cone penetrometer; after testing, soil cone indices of the disturbed soil resulting from the ripper passage were measured. A soil-ripper model was developed to simulate the field operation of the ripperand its interaction with soil using the discrete element method (DEM). The model was able to predict soil swell factor which is commonly used to evaluate the extent of soil loosening by a tillage tool. The model ripper was 1:1 scale representation of ripper used in the field tests, and the spherical model soil particles had diameters varying from 3 to 30 mm. The soil-ripper model was calibrated and validated through comparing soil cone indices measured in the field and thoseobtained through virtual penetration tests performed to the assembly of the model particles. The validated soilripper model was used to further investigate soil swell factor as affected by the ripper working depths under differentinitial soil porosities.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".