Policy and Regulations for Registration of Microbial Organisms in Denmark
Bibliographic record
Abstract
In Denmark several factors like the national pesticide action plan, ethical questions, national research strategy, increasing share of organic farming and fees are affecting the policy regarding regulatory agencies approach for products supporting sustainable pest management. The use of microbial pesticides in Denmark are limited, with the relatively largest share used in the greenhouse sector. Approval of a product not sold in Denmark before July 26, 1993 consists of two parts: An EU approval of the active micro-organism, and a national approval of the product containing the active micro-organism. An EU approval of an active micro-organism is only granted if the active micro-organism is included in Annex I of the directive of authorized active organisms. As a main principle, an active micro-organism shall be entered on the list of authorized active organisms before the Danish EPA may grant an approval for sale or import of products containing active micro-organisms. Until now five new organisms have been recommended for EU approval and inclusion in Annex I of the Directive, but so far none have been included. For products sold in Denmark before July 26, 1993 a transitional scheme specified in the Order is applied. Under this procedure application for approval of such products should be submitted to the Danish EPA before July 26, 1994 if the products were intended for sale in Denmark after this date. The application is considered at a national level only by the Danish EPA. The Danish EPA has received applications concerning nine different active micro-organisms. Both GMO's and biocides are covered by specifie legislation. If the GMO's are also pesticides, they must also comply with the Danish pesticides legislation. As no transgenic microbial pesticides or microbial biocides have yet been registered in Denmark, there is no legal practice on this issue.
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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 | 0.020 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.010 | 0.003 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.013 | 0.004 |
| Insufficient payload (model declined to judge) | 0.021 | 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".