Xylem function of arid‐land shrubs from California, USA: an ecological and evolutionary analysis
Bibliographic record
Abstract
Xylem traits were examined among 22 arid-land shrub species, including measures of vessel dimensions and pit area. These structural measures were compared with the xylem functional traits of transport efficiency and safety from cavitation. The influence of evolution on trait relationships was examined using phylogenetic independent contrasts (PICs). A trade-off between xylem safety and efficiency was supported by a negative correlation between vessel dimensions and cavitation resistance. Pit area was correlated with cavitation resistance when cross species data were examined, but PICs suggest that these traits have evolved independently of one another. Differences in cavitation resistance that are not explained by pit area may be related to differences in pit membrane properties or the prevalence of tracheids, the latter of which may alter pit area through the addition of vessel-to-tracheid pits or through changes in xylem conduit connectivity. Some trait relationships were robust regardless of species ecology or evolutionary history. These trait relationships are likely to be the most valuable in predictive models that seek to examine anatomical and functional trait relationships among extant and fossil woods and include the relationship among hydraulic conductivity and vessel diameter, between vessel diameter and vessel length, and between hydraulic conductivity and wood density.
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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 | 0.001 |
| 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) | 0.001 | 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".