Bibliographic record
Abstract
The bachelor thesis deals with oilseed rape - distribution of its production according to the countries of the world, NUTS EU regions and also distribution of its sowing areas in districts of the Czech Republic. It also deals with the development of oilseed rape production in the countries of the world (between 1961 and 2017), in the NUTS EU (2000-2017) and in the districts of the Czech Republic (1990-2019). The data sources are Faostat, Eurostat and Agrocenzus. The data are processed in the form of tables, development charts and especially cartographic products - cartodiagrams, cartograms of development and maps of localized points. Oilseed rape production in the world continues to grow. Canada is the largest producer, follows China and India, but the largest Production comes from the EU (mainly France, Germany and Poland), where it is concentrated in the central part of the European temperate zone. In the Czech Republic, oilseed rape is grown almost throughout the territory, except for mountain border areas, extensive agglomerations and other non-agricultural spaces.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.054 | 0.016 |
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".