Historical Developments of Flax Industry for Improving Fibers Quality and Fabrics Properties
Bibliographic record
Abstract
Flax (Linum usitatissimu) is one of the main crops in Canada for the production of linseed oil, which is used in food and chemical industries. The seeds are crushed to make linseed oil, and the remaining cake is used for fodder. Moreover, the boiling of seed oil is used in making paints, varnish and printing ink. The degradation of flax fibers is a crucial aspect in the development of natural fiber. Cellulose controls the major degradation behavior of flax fibers. Retting of flax is the separation of fibers and fiber bundles from non-fiber tissues in the stems. Bast fibers are processed by various means that may include retting, breaking, scutching, hackling, and combing. In order to bleach the flax and to keep the fiber tenacity high enough it is necessary to remove the lignin and partially to preserve the pectin. The problem of the classical hydrolyzing treatment with alkalis and oxidizers is due to the effect of these chemicals not only on the pectin and the lignin but also the cellulose itself resulting on the drastically decrease the material strength
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.029 | 0.015 |
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".