Selected properties of cattail fibre for biomedical applications
Bibliographic record
Abstract
Researchers at the University of Manitoba have developed a textile fibre from cattail biomass. The current study was primarily focused on investigating the possibility of utilizing an already used solution to extract fibres from cattail plants. Examination of physical and mechanical properties of extracted fibre was carried out, followed by an analysis of its chemical treatment effect through the application of 17th-time reuse of alkali solution. To check the suitability of re-used alkali solution, eight fibre properties, including yield percentage, contact angle, load at break, tensile stress at break, tensile strain at break, Young’s modulus, tenacity at break, and moisture regain were determined. One-way ANOVA was used to calculate average and standard deviations of eight properties for all 17th time reuse solutions as well as significant differences among the fibre properties obtained from reused alkali solutions. Data from descriptive statistics were programmed in Python computer language to find out reuse time for single and multiple properties. It was found that for single property, alkali solution can be reused up to R17 for yield (%), contact angle, moisture regain, and strain; R13 for tensile stress; and R14 for Young’s modulus. For multiple properties, the reuse time was found in decreasing order with the increasing in the number of properties.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.004 | 0.001 |
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".