Chemical composition of the epicuticular and intracuticular wax layers on the adaxial side of <i> Ligustrum vulgare </i>leaves
Bibliographic record
Abstract
Previous research has shown that cuticular triterpenoids are exclusively found in the intracuticular wax layer of Prunus laurocerasus. To investigate whether this partitioning was species-specific, the intra- and epicuticular waxes were identified and quantified for the glossy leaves of Ligustrum vulgare, an unrelated shrub with similar wax morphology. Epicuticular wax was mechanically stripped from the adaxial leaf surface using the adhesive gum arabic. Subsequently, the organic solvent chloroform was used to extract the intracuticular wax from within the cutin matrix. The isolated waxes were quantified using gas chromatography with flame ionization detection and identified by mass spectrometry. The results were visually confirmed by scanning electron microscopy. The outer wax layer consisted entirely of homologous series of very-long-chain aliphatic compound classes. By contrast, the inner wax layer was dominated (80%) by two cyclic triterpenoids, ursolic and oleanolic acid. The accumulation of triterpenoids in the intracuticular leaf wax of a second, unrelated species suggests that this localization may be a more general phenomenon in smooth cuticles lacking epicuticular wax crystals. The mechanism and possible ecological or physiological reasons for this separation are currently being investigated.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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 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".