Into the spongy-verse: structural differences between leaf and flower mesophyll
Bibliographic record
Abstract
As the site of almost all terrestrial carbon fixation, the mesophyll tissue is critical to leaf function. However, mesophyll tissue is not restricted only to leaves but also occurs in the laminar, heterotrophic organs of the floral perianth, providing a powerful test of how metabolic differences are linked to differences in tissue structure. Here, we compared mesophyll tissues of leaves and flower perianths of six species using high-resolution X-ray computed microtomography (microCT) imaging. Consistent with previous studies, stomata were nearly absent from flowers, and flowers had a significantly lower vein density compared to leaves. However, mesophyll porosity was significantly higher in flowers than in leaves, and higher mesophyll porosity was associated with more aspherical mesophyll cells. Despite these differences in cell and tissue structure between leaf and flower mesophyll, modeled intercellular airspace conductance did not differ significantly between organs, regardless of differences in stomatal density between organs. These results suggest that in addition to differences between leaves and flowers in vein and stomatal densities, the mesophyll cells and tissues inside these organs also exhibit marked differences that may allow for flowers to be relatively cheaper in terms of biomass investment per unit of flower surface area.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".