Inter and intra-population variation of leaf stomatal traits of Quercus robur L. in Northern Serbia
Bibliographic record
Abstract
The research involved the examination of inter- and intra-population variation of stomatal traits: stomatal density, stomatal length and width, stomatal pore surface, potential conductance index and stomatal shape coefficient, in Quercus robur L. leaves. The research was conducted in northern Serbia and included five populations (?Ada Ciganlija?, ?Bojcinska suma?, ?Subotica?, ?Sombor? and ?Vrsac?). The stomatal characteristics were examined in fully expanded leaves, from two leaf positions - the sun-exposed and shaded side of the tree. The leaf position in the tree crown, forming a part of the phenotypic variance, was relevant for the stomatal dimension traits. Within populations, the differences between the genotypes (i.e. trees), were relevant for all analyzed traits. On the basis of the analysis of the inter-populational differences, the ?Bojcinska suma? population had a statistically significantly lower stomatal density in comparison to the other populations.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".