Global Emerging HEmophilia Panel (GEHEP): A Multinational Collaboration for Advancing Hemophilia Research and Treatment
Bibliographic record
Abstract
GEHEP, established in 2009, is an independent, multi-institutional, international consortium of early career hematology specialists in the field of hemophilia and other inherited bleeding disorders. The main objective of the group, whose members practice at institutions in North America, Europe, and South Africa, is to advance hemophilia care by providing a forum for mentored collaborative research, developing programs for improving clinical care, and promoting academic career development of junior faculty. GEHEP members collect and document anonymized data on intra- and interinstitutional differences in patient populations, diagnosis, and treatment in the field of hemophilia and other bleeding disorders. To facilitate sharing of aggregated data among GEHEP members, a global protocol was developed and approved by most members' local institutional review board. Current GEHEP research initiatives are varied, encompassing work in pediatric and adult patients. GEHEP members have presented research at international meetings on the initiation of prophylaxis in children, use of immune tolerance induction in adults, and prevalence of acute coronary syndromes in older patients with hemophilia. The main goal of the continuing work of GEHEP is to advance the care of patients with hemophilia worldwide.
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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 | 0.005 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".