Recognition and differentiation of species in the <i>Passiflora sidifolia</i> complex
Bibliographic record
Abstract
The variation in leaf morphology observed in Passifloraceae is one of the most extreme cases in the Angiosperms, allowing some species within this family to be distinguished by their leaves. Nevertheless, other species in this family are difficult to recognize based solely on leaf morphology, or by floral and molecular characteristics. Aiming to verify the similarities and differences between the Passiflora species Passiflora actinia Hook., Passiflora elegans Mast., Passiflora sidifolia M.Roem., and Passiflora watsoniana Mast., detailed analyses were conducted regarding the morphological traits of the leaf blade, specifically shape and venation, and the flower. The data were composed of continuous and qualitative values, using the Gower coefficient. A principal coordinates analysis (PCoA) and cluster analysis were performed. Features that have not previously been used for the Passifloraceae, such as leaf venation, were important for the distinction of P. watsoniana from the other species. The analyses including only the species P. actinia, P. sidifolia, and P. elegans showed a clear differentiation between them. Despite the wide variability observed in P. elegans, the analysis revealed that the different populations from different regions had more similarities with each other than with any other species.
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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 | 0.001 | 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".