Nitrogen Application in Arugula Culture
Bibliographic record
Abstract
Vegetable development and productivity are influenced by several factors, including the nutrient amounts available. Providing adequate nitrogen favours vegetative growth and promotes increased productivity, in addition to providing greater succulence and improving leaf quality. This work evaluated the effect of nitrogen doses and sources on arugula culture development and productivity. The experiment was conducted on the experimental farm at the State University of Goiás, Ipameri campus, in the municipality of Ipameri, Goiás state (GO). The experiment used a 2 × 5 factorial randomized complete block design, with two sources (normal urea and coated urea), five nitrogen doses (0, 60, 120, 180 and 240 kg ha-1 of N) and four replicates. Plant height, stem diameter, leaf number, fresh shoot matter, dry shoot matter and productivity were evaluated. The results obtained here suggest that nitrogen sources do not influence arugula culture development, but nitrogen doses influence the arugula culture’s productive characteristics.
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How this classification was reachedexpand
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".