An International Framework for Data Sharing: Moving Forward with the Global Alliance for Genomics and Health
Bibliographic record
Abstract
The Global Alliance for Genomics and Health is marshaling expertise in biomedical research and data sharing policy to propel bench-to-bedside translation of genomics in parallel with many of the BioSHaRE-EU initiatives described at length in this Issue. Worldwide representation of institutions, funders, researchers, and patient advocacy groups at the Global Alliance is testament to a shared ideal that sees maximizing the public good as a chief priority of genomic innovation in health. The Global Alliance has made a critical stride in this regard with the development of its Framework for Responsible Sharing of Genomic and Health-related Data.(1) This article first discusses the human rights pillars that underlie the Framework and mission of the Global Alliance. Second, it outlines the Global Alliance's use of data governance policies through a number of demonstration projects. Finally, the authors describe how the Global Alliance envisions international data sharing moving forward in the postgenomic era.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".