Bibliographic record
Abstract
In Europa wordt belasting geheven op energie.De belastingen voor de belangrijkste energiesoorten in de glastuinbouw in de landen in Noordwest-Europa zijn onderzocht.In de afzonderlijke landen worden door de glastuinbouw verschillende brandstoffen ingezet, warmte en elektriciteit ingekocht en wkinstallaties gebruikt.De energiebelasting vertoont grote verschillen tussen landen en tussen energiesoorten per land.Verlaagde tarieven of vrijstellingen voor de glastuinbouw zijn er in alle onderzochte landen.In het algemeen zijn de kosten voor energiebelasting het hoogst in Denemarken, gevolgd door het Verenigd Koninkrijk, Nederland, Duitsland, Frankrijk, België en Polen.Bezien vanuit de energiebelasting is er in Noordwest-Europa geen gelijk speelveld voor glastuinbouwbedrijven.In Europe, a tax is levied on energy.The taxes levied on the most essential forms of energy in the greenhouse horticulture sector in the countries of north-western Europe have been examined.The greenhouse horticulture sectors in individual countries use various types of fuels, purchase heat and electricity and utilise CHP installations.There are significant differences in the energy taxes of different countries and between the different forms of energy per country.Reduced rates and exemptions for the greenhouse horticultural sector exist in each of the countries that were examined.Generally, the costs of energy tax are the highest in Denmark, followed by the United Kingdom, the Netherlands, Germany, France, Belgium and Poland.In terms of energy taxes, north-western Europe does not offer greenhouse horticultural holdings a level playing field.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".