Evaluation of the Ornamental Potential of Basil Grown in Field in the Federal District
Bibliographic record
Abstract
Basil is commonly known and cultivated as a spicy and aromatic plant. However, ornamental use is possible in landscape projects. The advancement of new technologies highlighted the production of ornamental plants in Brazil, and among these stands are basil, a species commonly known for its spicy and aromatic properties. Nonetheless, with the increase in the demand for plants with multiple functions in the ornamental plant market, more studies are needed to evaluate the potential of this species. This work evaluated phenotypic characteristics to promote studies and elaborate technical manuals on growing basil for ornamental use. Therefore, an experiment was carried out at the Agua Limpa Farm (FAL) of the University of Brasilia (UnB), located in the Federal District, Brazil. Two genotypes were cultivated, Folha Fina (thin-leaf) and Folha Larga (broad-leaf) from Topseed Garden®, and the following characteristics were evaluated: canopy shape, leaf texture, stem, inflorescence, flower and leaf color, and leaf gloss. The evaluated genotypes did not show significant differences in stem (green), inflorescence (green), and flower colors (white). However, they showed differences in leaf color, with dark green leaves and thin, light green leaves. Both basil genotypes (Ocimum basilicum L.) have ornamental potential due to their favorable phenotype characteristics.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".