Feasibility of polymer-coated urea (ESN) for agronomic and environmental considerations in the parkland region of Saskatchewan
Bibliographic record
Abstract
Background• Most prairie soils are deficient in plant-available nitrogen (N).• Therefore N-fertilizer application is necessary to optimize crop yield.• However, the N-use efficiency (NUE) from applied fertilizers is usually less than 50% in the year of application.• Improving NUE is critical to: o increase economic returns o minimize environmental damage from fertilizer-N moving from the soil to water and air Urea as a nitrogen source• Urea (uncoated) is the most common dry nitrogen (N) fertilizer in Saskatchewan's Parkland Region in large part due to price.• One-pass combined seeding and fertilizer application (i.e.direct seeding) allows for placement of seed and fertilizer in the same or separate bands in the soil.• The advantage is that subsoil urea fertilizer placement reduces volatilization losses of N and improves fertilizer use efficiency.• Seed-placement of urea is a popular option.• However, close proximity of urea to seed can result in seedling damage, reduce seedling emergence (also known as seedling density, stand density, plant density), or reduce yield when applied at rates to satisfy the crop's N-demand for the season. Polymer-coated urea: what is it?• Polymer-coated urea (PCU) is a urea granule (prill) coated in a flexible, thin, porous polymer membrane or coating.• Water passes through the coating to create a urea-water solution.• The coating then controls the release rate of the fertilizer solution into the soil.• Temperature and soil moisture are the major factors that control the release rate -the same major factors that affect plant growth.• In theory, fertilizer release is synchronized to plant needs.
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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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".