SIMULATIONS OF TRANSITIONS FROM REGULAR TO STOCHASTIC PHYLLOTACTIC PATTERNS
Why this work is in the frame
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Bibliographic record
Abstract
The paper deals with a statistical method to analyze irregular phyllotactic patterns. To characterize the degree of order in phyllotactic systems, we determine the variation of the angle of divergence of a given leaf with regard to the preceding one. By knowing the range of uncertainty of the angle of divergence, it is possible to determine from which leaves rank a system becomes completely disorganized. We show that there is a quantitative link between the degree of uncertainty of the angle of divergence, and the number of regularly and randomly distributed leaves. To quantify this relationship, we deduced a formula from numerical simulations involving different ranges of uncertainty that can be observed in the angle of divergence in three different phyllotactic patterns: distichous (two orthostichies), opposite-decussate (four orthostichies) and spiral (137°). A χ 2 statistical test allows us to determine the threshold of transition between ordered and disordered phyllotactic patterns with a fixed level of confidence. By using the sho mutants described by Itoh et al. 1 as a case study, we show that this formula is useful mainly for analyzing the degree of order in phyllotactic mutants from two complementary points of view: the number of regularly distributed leaves and the degree of uncertainty of the divergence angle.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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