Organ Donation Organization Architecture: Recommendations From an International Consensus Forum
Bibliographic record
Abstract
This report contains recommendations from 1 of 7 domains of the International Donation and Transplantation Legislative and Policy Forum (the Forum). The purpose is to provide expert guidance on the structure and function of Organ and Tissue Donation and Transplantation (OTDT) systems. The intended audience is OTDT stakeholders working to establish or improve existing systems. Methods: The Forum was initiated by Transplant Québec and co-hosted by the Canadian Donation and Transplantation Program partnered with multiple national and international donation and transplantation organizations. This domain group included administrative, clinical, and academic experts in OTDT systems and 3 patient, family, and donor partners. We identified topic areas and recommendations through consensus, using the nominal group technique. Selected topics were informed by narrative literature reviews and vetted by the Forum's scientific committee. We presented these recommendations publicly, with delegate feedback being incorporated into the final report. Results: This report has 33 recommendations grouped into 10 topic areas. Topic areas include the need for public and professional education, processes to assure timely referral of patients who are potential donors, and processes to ensure that standards are properly enforced. Conclusions: The recommendations encompass the multiple roles organ donation organizations play in the donation and transplantation process. We recognize the diversity of local conditions but believe that they could be adapted and applied by organ donation organizations across the world to accomplish their fundamental objectives of assuring that everyone who desires to become an organ donor is given that opportunity in a safe, equitable, and transparent manner.
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 | 0.274 | 0.265 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.005 |
| Bibliometrics | 0.012 | 0.009 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.017 | 0.020 |
| Open science | 0.009 | 0.014 |
| Research integrity | 0.028 | 0.021 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".