Organ Donation and Transplantation in Canada: Insights from the Canadian Organ Replacement Register
Bibliographic record
Abstract
PURPOSE OF REVIEW: To provide an overview of the transplant component of the Canadian Organ Replacement Register (CORR). FINDINGS: CORR is the national registry of organ failure in Canada. It has existed in some form since 1972 and currently houses data on patients with end-stage renal disease and solid organ transplants (kidney and/or non-kidney). The transplant component of CORR receives data on a voluntary basis from individual transplant centres and organ procurement organizations across the country. Coverage for transplant procedures is comprehensive and complete. Long-term outcomes are tracked based on follow-up reports from participating transplant centres. The longitudinal nature of CORR provides an opportunity to observe the trajectory of a patient's journey with organ failure over their life span. Research studies conducted using CORR data inform both practitioners and health policy makers alike. IMPLICATIONS: The importance of registry data in monitoring and improving care for Canadian transplant candidates/recipients cannot be over-stated. This paper provides an overview of the transplant data in CORR including its history, data considerations, recent findings, new initiatives, and future directions.
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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 | 0.008 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.038 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".