Does Handling Physically Alter the Coating Integrity of ESN Urea Fertilizer?
Why this work is in the frame
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Bibliographic record
Abstract
Environmentally smart nitrogen (ESN) is a polymer‐coated form of N that provides controlled‐release, allowing higher seed‐placed safe rates of urea fertilizer. The influence of coating integrity on the rate of N release in field conditions is unknown. Field studies were conducted from 2008 to 2011 near Lethbridge, AB, Canada, to determine the impact of handling methods on the polymer coating of ESN when seed‐placed with canola ( Brassica napus L.), wheat ( Triticum aestivum L.), or triticale (X Triticosecale Wittmack). Abrasion levels were created through laboratory simulation (0–80% N release after 7d in 23°C water, calibrated in increments of 10%; Exp. 1), or from handling by collecting ESN from exit points on nine implements, which was subjected to two methods of loading and unloading at the retail point and farm (9 × 2 × 2 factorial; Exp. 2). Nitrogen release data was related to plant responses in the field by seed placing the ESN at rates of 45 kg N ha −1 with canola and 90 kg N ha −1 for cereals. At the highest N release treatment in Exp. 1, winter cereal and canola stands were reduced by ∼30% and spring cereals by 18%. Grain yield was unaffected in winter wheat but reduced in canola and spring cereals by 20 and 10%, respectively. In Exp. 2, abrasion from transferring ESN in equipment containing scaly deposits or seeders configured with header‐manifold systems operating at high fan speeds corresponded to higher N release treatments, which reduced winter wheat and canola stands. Crop injury and grain yield, however, was usually mitigated through proper equipment maintenance and settings.
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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 | 0.000 | 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 it