Bibliographic record
Abstract
Le Danemark compte 71 conventions fiscales en vigueur, ainsi que l’indique sa réponse au questionnaire d’examen par les pairs, y compris la Convention nordique multilatérale conclue avec la Finlande, l’Islande, la Norvège et la Suède (la « Convention nordique ») Voir la convention multilatérale conclue par le Danemark, la Finlande, les Îles Féroé, l’Islande, la Norvège et la Suède tendant à éviter la double imposition concernant les impôts sur le revenu et la fortune (1996, 1997, 2008 et 2018). Au total, le Danemark a identifié 74 « accords » dans sa liste des conventions fiscales : 70 conventions bilatérales et la Convention nordique conclue avec quatre de ses partenaires.. 19 de ces conventions, celles conclues avec l’Australie, la Belgique, le Canada, l’Inde, l’Irlande, Israël, le Japon, la Lituanie, le Luxembourg, Malte, la Nouvelle-Zélande, les Pays-Bas, la Pologne, la République slovaque, le Royaume-Uni, la Serbie, la Slovénie, l’Ukraine et la Convention nordique sont conformes au standard minimum.
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 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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.574 | 0.324 |
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".