Variability of potato petiole nitrogen in response to nitrogen fertilizer, implications for variable management
Bibliographic record
Abstract
Recent increases in the cost of fertilizer nitrogen have prompted producers to assess the \npotential to vary inputs in space and time to produce the highest marketable yield of \npotatoes. A study was conducted from 2005 to 2007 near Brandon, Manitoba Canada, to \nassess the spatial variability of potato yield in upper, middle and lower landforms on a \nsandy loam soil in response to a range of nitrogen fertilizer rates and split application. \nPetiole nitrogen, determined late in the growing season, was correlated with potato yield \nand was used to assess nitrogen sufficiency through the growing season. Petiole nitrogen \nvaried with time during the growing season, from uniform levels in June across all \nfertilizer treatments, to those which varied with fertilizer treatment in July and August. \nFurthermore potato petiole nitrogen was higher in lower landforms during July and \nAugust, where higher total and marketable yields were recorded. The potential for split \napplication of nitrogen in potatoes based on management zones or sensor readings will \nhave to be carefully assessed to account for temporal and spatial variability.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 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".