El Grupo del Artículo 29 y la Norma de protección de datos del Código AMA.
Bibliographic record
Abstract
El denominado Grupo del Articulo 29 (que reune fundamentalmente a las autoridades de proteccion de datos de la Union Europea) se ha pronunciado en dos dictamenes (uno de 2008 y otro de 2009) sobre la compatibilidad con la Directiva 95/46/CE, relativa a la proteccion de las personas fisicas en lo que respecta al tratamiento de datos y a la libre circulacion de estos datos del (entonces) proyecto de Norma internacional para la proteccion de la intimidad y los datos personales elaborado por la Agencia Mundial Antidopaje, en relacion con el Codigo Mundial Antidopaje (AMA) y la base de datos ADAMS (Anti-Doping Administration & Management System) situada en Montreal, Canada, cuya informacion es facilitada y accesible por las organizaciones antidopaje. En ambos dictamenes, el Grupo del Articulo 29 concluyo que la norma analizada no era compatible con el nivel de proteccion exigido por la Directiva 95/46/CE. El Grupo del Articulo 29 subrayo que los responsables (tales como las organizaciones antidopaje) de la UE tienen el deber de tratar los datos de acuerdo con la ley nacional y por lo tanto no deben tener en cuenta el Codigo AMA y las normas internacionales en la medida en que se opongan el ordenamiento nacional.
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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 | 0.028 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.008 |
| Scholarly communication | 0.011 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 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".