Effects of multiple passes of vehicles on clay soil compaction as measured by dry bulk density.
Bibliographic record
Abstract
Effects of multiple passes of vehicles on clay soil compaction as measured by dry bulk density.Canadian Biosystems Engineering/Le génie des biosystèmes au Canada 55: 2.17-2.22.Soil compaction caused by machinery traffic on agricultural soil is becoming a problem in all parts of the world.In this experiment, vertical distribution of machinery-induced compaction on clay soil was investigated.The weights of the machineries used during the experiment were 82.80 kN (light vehicle or L) and 132.34 kN (heavy vehicle or H).Both machines passed repeatedly (1, 2, 4, 8 times) on the same track of the soil at two different moisture contents known as dry and wet plots of the farmland.The different parameters measured during the experiment were dry bulk density, vehicle axle load, and track width of the wheel traffic.The results showed that in a wet soil profile the dry bulk density of the soil taken to a depth of 0.30 m showed a statistically significant difference (p < 0.05) relative to the control (zero traffic zone).But it requires at least two passes by the same vehicles to obtain a statistically significant difference (p < 0.05) on the dry soil.Key words: Repeated traffic, Soil compaction, Axle load Le compactage du sol causé par la circulation des équipements sur les sols agricoles est devenu un problème dans toutes les parties du monde.Dans cette étude, la distribution verticale du compactage produit par la machinerie a été évaluée dans un sol argileux.Le poids des machines utilisées durant l'expérience étaient respectivement de 82,80 kN (véhicule léger ou L) et 132,34 kN (véhicule lourd ou H).Les deux machines passaient de manière répétitive (1, 2, 4, 8 fois) dans les mêmes voies sur des sols à deux teneurs en eau différentes et déterminées soit des parcelles sèches et humides de terre agricole.Les paramètres mesurés durant l'expérience étaient la densité apparente sèche, la charge sur l'essieu du véhicule et la largeur de l'empreinte de la roue.Les résultats ont montré que dans un profil de sol humide la densité apparente sèche du sol pris à une profondeur de 0,30 m présentait une différence statistiquement significative (p < 0,05) lorsque comparée au témoin (zone sans circulation).Cependant deux passages par le même véhicule étaient nécessaires pour qu'une différence statistiquement significative soit obtenue avec le sol sec.Mots clés: circulation répétée, compactage du sol, charge à l'essieu.
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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 | 0.001 |
| 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) | 0.001 | 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".