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.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".