Influence of Stem Diameter on Fiber Diameter and the Mechanical Properties of Technical Flax Fibers from Linseed Flax
Bibliographic record
Abstract
The continued search for sustainable and eco-friendly materials has led to the integration of bio-fibers, such as flax fiber, as reinforcement in composite materials; however, a wide variation in their diameters and mechanical properties poses a considerable challenge for their incorporation in load bearing and structural bio-composite materials. In this paper, a rigorous experimental investigation was performed using two varieties of linseed flax from two growing locations to determine if the variations observed in ultimate tensile strength, Young’s modulus, failure strain and diameter could be attributed to the diameters of the stems that produced the fibers. Tests were performed in two different facilities and the results were compared and analyzed using Welch’s t-tests. Results showed that samples which differed by stem diameter had statistically significant positive correlation with fiber diameter and negative correlation with tensile strength. No correlations for tensile strength, Young’s modulus or fiber diameter were found in samples with the same stem diameter range that were grown in different locations or were of different varieties, that is the effect of location and variety is not statistically significant. Failure strain did not show any statistical significance with respect to differences in stem diameter and only showed one statistically significant result between both facilities for one of the two growing location comparisons.
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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 | 0.001 |
| 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".