Knitted Denim Fabrics: Fabrication Process and Fibrous Influence on Several Properties of the Fabric
Why this work is in the frame
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Bibliographic record
Abstract
Denim-like knitted fabrics are getting popular for their several favorable properties, such as flexibility, comfort, and ease of manufacturing. This study aimed to manufacture knitted denim fabrics made from various blend ratios of cotton, polyester, and spandex fibers. Seven fabrics with a fiber blend ratio ranging from 95% cotton/5% spandex to 30% cotton/65% polyester/5% spandex were developed using a weft circular knitting machine. First, the twill effect of the knitted denim fabric was brought by following a cross terry knitting structure to produce each fabric sample of this study. After that, the fabric performance was analyzed by characterizations, such as areal density, pilling and abrasion resistance, dimensional stability, stretch, and recovery, tear strength, bursting strength, air permeability, vertical wicking, liquid absorbency capacity, and different colorfastness tests. The results showed that different cotton, polyester, and spandex fiber compositions did not significantly affect knitted denim fabrics’ weight per unit area, abrasion resistance, and different color fastness properties. However, the elongation and vertical wicking test data showed that the knitted denim fabrics with a higher cotton fiber ratio were better. However, the results from shrinkage, spirality, pilling, recovery, strength, air permeability, and liquid absorbency capacity tests revealed the benefits of having a higher polyester fiber ratio in the cotton/polyester/spandex blended knitted denim fabrics. One-way analysis of the variance test was also performed on the generated data of this study and reported in the respective section of the article.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it