Modeling the Recommendation of Nutrients for Cabbage (Brassica oleracea) Crop
Bibliographic record
Abstract
Cabbage presents high nutrients demand, which requires proposal of recommendation models that are compatible with current productive potential. The objective of this study was to propose a nutritional balance model to recommend nutrients for cabbage. In order to estimate fertilizer recommendation, the system considered the requirement subsystem (REQ), which includes the crop demand and recovery efficiency (RE) of the applied nutrient, and supply subsystem (SUP), which corresponds to the nutrient supply by soil and crop residues. To determine the attributes needed to estimate nutritional demand, values were obtained from literature and from two experiments, one with nitrogen (N) and one with potassium (K). The fertilizer recommendation for N, P and K consisted in the difference between REQ and SUP. For the other nutrients, the system presented only crop export and extraction and not the REQ due to scarcity of data regarding RE. The modeling is a useful tool for recommending fertilization for cabbage and is subject to constant improvements.
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 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 | 0.001 | 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 | 0.001 | 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".