Characteristics of Soil Pockets Resulting from the AerWay Rolling Tines
Bibliographic record
Abstract
Abstract. Soil aerators have recently been adapted for land application of liquid manure. Characteristics of the soil pockets formed by the aerator affect the manure infiltration, placement, and potential manure application rate. A two-year field study was carried out to evaluate factors affecting pocket characteristics in two forage fields in Manitoba, Canada; one field had a clay loam soil, and the other had a loamy sand soil. An AerWay aerator with two types of rolling tines (shatter and leaf tines) was used in the field study. Each type of rolling tine was operated at two different swing angles (0° and 5°) and two penetration depths (125 and 150 mm). The characteristics of the resultant soil pockets including pocket opening dimensions and pocket volume were measured. Pocket opening varied between 91 and 212 mm in length, 9 and 44 mm in width, and 1,088 and 5,555 mm2 in area. The volume of pocket also varied with the soil type, tine type, penetration depth, and swing angle, and ranged between 69 and 327 mL. Larger pocket openings and volumes were observed in the clay loam soil than in the loamy sand soil. The shatter tines created larger soil pocket volumes than the leaf tines. The larger swing angle and greater penetration depth resulted in larger soil pockets.
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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".