Joint Communication from Davos Cardiology Update, February 2017
Bibliographic record
Abstract
At the Davos Cardiology Update Meeting in February 2017, Prof. Salim Yusuf from Hamilton Ontario gave two presentations. He provided permission to record and use the talk on the HOPE-3 trial for educational purposes. However, he explicitly declined to give permission to video tape, reproduce, or broadcast his talk on diet and cardiovascular disease because it included preliminary and unpublished analyses from the large PURE study that he and approximately 200 investigators have been conducting for over 12 years. These analyses are ongoing and it is expected that the articles from the study will be submitted for publication soon after extensive checks, updates of follow up data, and further analyses. It is prudent for commentators to wait for the publication to objectively assess the detailed methods and the findings, and also place it in the context of meta analyses or summaries of other similar studies. The Zurich Heart House apologizes for inadvertently videotaping the presentation by Prof. Yusuf and placing it on YouTube without explicit permission. The title of the YouTube post was not provided to Prof. Yusuf and he was not aware of it until after it was posted. The video was immediately removed from YouTube by ZHH and joint efforts were made to ban the copied content.
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 | 0.006 | 0.047 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.139 | 0.118 |
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".