543 Effect of Calcium and Sulfur on Yield of Late-storage Cabbage
Bibliographic record
Abstract
Soil and crop management practices suggest the possibility of sulfur deficiency for cole crops in Southern Ontario. A 3-year study was conducted to evaluate rates of calcium and sulfur on yield of `Huron' late-storage cabbage. Treatments were based on CaSO 4 applied at 0, 1000, 2000, and 3000 kg·ha –1 `Novacal' (Ca 27%, S 19%, Mg 2.5%, Dolomex Inc., Portage-du-Fort, Quebec, Canada), a granulated gypsum product. Potassium sulfate and calcium nitrate were used as elemental controls. Potassium and nitrogen levels were balanced with potassium chloride and ammonium nitrate. Phosphorous applications were based on soil analysis. All treatments were applied pre-plant incorporated. This trial was repeated on sand and loam soils typical of soil used for cabbage production in southern Ontario. Applications of sulfur increased yield of cabbage on sand and clay, although the optimum rate varied from year to year. Medium and high rates produced the highest yield in the first year, while low rates were more effective in the second and third seasons. Response of cabbage to calcium varied from year to year. Medium and high rates of calcium increased yield on sand, but had no effect on clay in the first year. Calcium had no effect on yield on either soil type in the second year. However, in the third year, low rates of calcium produced the highest yield on both sand and clay. Although there were no visual symptoms of deficiency, applications of sulfur, and to a lesser extent calcium, increased yield indicating that a `hidden hunger' for these elements may exist on some soils in southern Ontario.
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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 | 0.000 |
| 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".