Vein‐to‐blade ratio is an allometric indicator of leaf size and plasticity
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PREMISE: As a leaf expands, its shape dynamically changes. Previously, we documented an allometric relationship between vein and blade area in grapevine leaves. Larger leaves have a smaller ratio of primary and secondary vein area relative to blade area compared to smaller leaves. We sought to use allometry as an indicator of leaf size and plasticity. METHODS: We measured the ratio of vein-to-blade area from the same 208 vines across four growing seasons (2013, 2015, 2016, and 2017). Matching leaves by vine and node, we analyzed the correlation between the size and shape of grapevine leaves as repeated measures with climate variables across years. RESULTS: The proportion of leaf area occupied by vein and blade exponentially decreased and increased, respectively, during leaf expansion making their ratio a stronger indicator of leaf size than area itself. Total precipitation and leaf wetness hours of the previous year but not the current showed strong negative correlations with vein-to-blade ratio, whereas maximum air temperature from the previous year was positively correlated. CONCLUSIONS: Our results demonstrate that vein-to-blade ratio is a strong allometric indicator of leaf size and plasticity in grapevines measured across years. Grapevine leaf primordia are initiated in buds the year before they emerge, and we found that total precipitation and maximum air temperature of the previous growing season exerted the largest statistically significant effects on leaf morphology. Vein-to-blade ratio is a promising allometric indicator of relationships between leaf morphology and climate, the robustness of which should be explored further.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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