Canadian government ordered to release unpublished Tamiflu data in landmark ruling
Bibliographic record
Abstract
The Canadian government has been instructed to release unpublished clinical trial data relating to Tamiflu, Relenza, and three human papillomavirus vaccines immediately, in a landmark ruling hailed as a “major victory” for transparency. The case was brought by Peter Doshi, assistant professor at the University of Maryland and associate editor of The BMJ , after Health Canada refused his request to obtain unpublished information relating to Tamiflu, Relenza, Gardasil, Gardasil 9, and Cervarix because he would not sign a confidentiality agreement that would have prevented him from disseminating or publishing anything on it. A federal court judge said it was “unreasonable” for Health Canada to impose a confidentiality requirement as a condition for the disclosure …
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 | 0.015 | 0.056 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.014 | 0.005 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.028 | 0.020 |
| Insufficient payload (model declined to judge) | 0.011 | 0.003 |
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".