Pro-Environmental and Health-Promoting Grounds for Restitution of Flax (Linum usitatissimum L.) Cultivation
Bibliographic record
Abstract
The current state of the world's ecosystems requires many measures to restore opportunities, if not for their reconstruction, then to stop the rate of biodiversity loss.One of the areas where this should happen is industrial agriculture.In order to diversify the large-scale monoculture crops dominated by cereals and fodder crops, science and practice draw attention to the need to introduce the plants of smaller or marginal significance into cultivation.Flax (Linum usitatissimum L.) is a species with special properties and great utility from the ancient times to the present.Currently, Canada is the largest producer of flax in the world, while France, Belgium and the Netherlands in Europe.The aim of the work was to assess the state of its cultivation (area and volume of production) and determine the possibilities of restituting this species in Poland.The analysis of the available materials indicates that the largest areas of flax cultivation occurred in the nineteenth and twentieth centuries, when flax competed with cotton as a raw material for the production of textile products.In the interwar period, Poland had a well-developed linen industry for flax processing.Large quantities of high-quality linseed oil were also produced.In the 1990s, the production of flax amounted to several hundred hectares, and after Poland's accession to the EU, the area of cultivation and production of oil flax increased.Bearing in mind the pro-environmental qualities of linen and linseed oil, there is a need to popularize this species and increase the cultivation area, for which the climatic and soil conditions in moderate climate are very favorable.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".