Evaluation of a sprayable elemental sulfur fertilizer under field conditions in Alberta
Bibliographic record
Abstract
Elemental sulfur (ES) fertilizers have high S content but may not be effective in the year of application due to the time required to oxidize. Rapid oxidation may be possible if the ES has a large surface area in contact with the soil. We evaluated the efficacy of Sulgro 70, a micronized ES fertilizer that is sprayed onto the soil surface, in eight field trials in southern and central Alberta over a 2 yr period. Under dry conditions in southern Alberta, the relative efficacy of Sulgro 70 to increase S supply to ion-exchange membranes was 22% during the first 4 wk period after seeding and 53% during the second 4 wk period after seeding, compared with ammonium sulfate (AS) sprayed on the soil surface. Under wetter conditions in central Alberta, the relative efficacy of Sulgro 70 to increase S supply was variable (51%–201%) during the first 4 wk period after seeding and 56% during the second 4 wk period after seeding. Based on increases in biomass S concentration in three trials where the unfertilized control had low S concentration (<3 g S·kg−1), the relative efficacy of Sulgro 70 was 34%. Canola seed yield was not increased by application of AS or Sulgro 70 in any of the trials. Sulgro 70 sprayed on the soil surface oxidized appreciably during the first 8 wk after seeding and, with suitable management, has the potential to meet canola S requirements in the year of application.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".