Growth and Visual Symptoms of Macro Deficiencies and Micronutrientes in Mallow (Urena lobata) Plants, Variety BR-01
Bibliographic record
Abstract
Within the increase of Coffee production and its export as well, a larger resourcefulness is been required to manufacture its bags. Due to these increases, a natural fiber source became valued again despite its growing had been forgotten for some years. The mallow is being observed as an excellent ecological alternative, but the knowledge of its handling and natural requirements are restricted, by the fact of lately inattention in this natural fiber. In this context with the purpose of contributing with the knowledge of this cultivation, an experiment was settled aiming to evaluate its growth, to characterize the visual of macro and micronutrients deficiency symptoms to determine the analytical levels of these nutrients. The mallow plants, variety BR-01, were cultivated in the Department of Soil’s greenhouse from Universidade Federal Rural da Amazônia-UFRA, in plastic vases containing 3 kg of ground silica and submitted to the following treatments: complete, omission of N, omission of P, omission of K, omission of Ca, omission of Mg, omission of S, omission of B, omission of Cu, omission of Fe, omission of Mn and omission of Zn. After a period comprehended between 7 and 29 days, the occurrence of deficiency symptoms has started, except for the treatments with omission of S, Cu and Zn. The plants development were mostly affected by the treatments with omission of B and Ca.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".