Leaf shape analysis using the multiscale Minkowski fractal dimension, a new morphometric method: a study with <i>Passiflora </i>(Passifloraceae)
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Bibliographic record
Abstract
A new method is proposed for the extraction of morphometric characteristics of plant leaf structures. A sample of 10 species of the genus Passiflora (P. coriacea Juss., P. foetida L., P. miersii Mast., P. organensis Gardner, P. pohlii Mast., P. suberosa L., P. amethystina J.C. Mikan, P. caerulea L., P. gibertii N.E.Br., P. maliformis L.) was used in an experiment to test the method. This genus shows a wide range of leaf forms, but there are some species pairs or groups whose morphological similarity makes their correct identification difficult. The multiscale function of the Minkowski fractal dimension was applied to digital images of leaves to generate complexity measures of their internal (veins) and external (leaf outline) form. The results of the leaf characteristic extraction method, as well as its potential as the basis for an identification mechanism, are discussed for the 10 species. The method was very accurate in correctly differentiating among species, since no leaf was erroneously identified. A small number of leaves per species was sufficient for establishing a characteristic pattern for each of them, which constitutes an important advantage of the method in the recognition and classification procedure.Key words: image processing, fractal dimension, plant taxonomy, morphometry, Passiflora.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| 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 it