Bibliographic record
Abstract
Theoretical models of phyllotaxis are based on geometric regularities appearing at the level of the shoot apical meristem (SAM). However, one cannot forget the presence of perturbed patterns in many plants. Disorganized patterns found in mutants of Arabidopsis and Antirrhinum bring new theoretical problems that cannot be solved by using models developed to analyse regular phyllotactic patterns. One way to take into account the perturbed patterns is to use a probabilistic approach to phyllotaxis. This review will focus mainly on recent probabilistic approaches that can be used to analyse perturbed patterns found in the plant kingdom in general and in phyllotactic mutants in particular. More precisely, it will be shown how probabilistic approaches can be used to determine the degree of order of phyllotactic patterns. By using particular tests, it is possible to statistically differentiate between whorled and distichous patterns (aggregated dispersion), spiral patterns (uniform dispersion), and random patterns (random dispersion). The elaboration of a general probabilistic model of phyllotaxis represents a new challenge for both theoretical and experimental research.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".