Leaf epidermal characters of Brazilian species of <i>Solanum</i> section <i>Torva</i> as taxonomic evidence
Bibliographic record
Abstract
To evaluate their taxonomic significance, the yet unknown epidermal characters of the leaves of 10 species of Solanum section Torva Nees (Solanaceae) from Brazil were determined using light and scanning electron microscopy. Our results indicated that the leaf epidermis showed epidermal cells of straight to wavy outlines. The curved pattern of anticlinal cell walls was predominant on the adaxial surface, and the wave pattern was predominant on the abaxial surface. Leaves are amphistomatic in six species ( Solanum acutilobum Dunal, Solanum bonariense L., Solanum guaraniticum A. St.-Hil., Solanum metrobotryon Dunal, Solanum scuticum M. Nee, and Solanum torvum Sw.) and hypostomatic in four species ( Solanum adspersum Witasek, Solanum paniculatum L., Solanum subumbellatum Vell., and Solanum variabile Mart.). Four different types of stomata (anisocytic, anomocytic, paracytic, and diacytic) were recognized, with the anisocytic type predominant on adaxial and abaxial surfaces. The combination of some micro-morphological characters such as density, distribution and type of stellate trichomes, the anticlinal walls of epidermal cells, and also the type and distribution of stomata proved to be the most useful and distinctive characters for the separation of species. This set of characters also may help as additional support in quality control of species having medicinal importance.
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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 | 0.002 | 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".