Setting the scene: Historical overview of challenges and what led to advances in comprehensive care in developed countries, the Canadian experience
Bibliographic record
Abstract
The history of the development of comprehensive care for hemophilia and other inherited bleeding disorders in Canada has been long and full of challenges. From limited in-patient treatment with plasma and cryoprecipitate in a few major centres in the 1950s and 1960s, a network of Hemophilia Treatment Centres (HTCs) offering multi-disciplinary comprehensive care, home infusion and prophylaxis was established across the country by the late 1970s and early 1980s, only to be shaken by the widespread contamination of factor concentrates with HIV and HCV in the 1970s and 1980s. In recent years the mission of HTCs has expanded to better serve people with von Willebrand disease, rare factor deficiencies and other rare bleeding disorders, and more fully recognize the needs of women with bleeding disorders. In 2020, challenges remain, notably maintaining the resources and expertise in HTCs and gaining access to the latest innovations in treatments.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.010 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".