Evidence and quantitative evaluation of tensile maturation strain in flax phloem through longitudinal splitting
Bibliographic record
Abstract
The stems of flax (Linum usitatissimum L. cv. ‘Mogilevsky’) contain many gelatinous fibers in their phloem. These fibers are important for the mechanical stability of the plant as well as for industrial applications. Gelatinous fibers are known to have a motor function in the xylem of trees and in many plant organs. This function arises from the so-called maturation strain, i.e., the tendency of the gelatinous layer to shrink during fiber maturation, resulting in a state of residual tensile stress. However, the occurrence of tensile maturation strain in flax phloem fibers remains to be demonstrated, and its magnitude has never been evaluated. Here we present a novel method to highlight and quantify this strain. The method consists in splitting a stem segment longitudinally, and measuring the curvature of the half segments through their opening distance. By using a mechanical model, the maturation strain can be calculated from the curvature, the dimensions of the component tissues, and their elastic properties. The model is validated by the agreement between model predictions and observations. The splitting experiment provides qualitative evidence that flax phloem develops tensile stress during maturation, just as xylem gelatinous fibers do. Calculations enable quantitative estimation of the maturation strain. The magnitude of this strain for the material studied is, on average, –1.5%.
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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 | 0.000 | 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".