Acceptance of Gold Medal From the Catalan Society of Transplantation by Drs. Lorraine Racusen and Kim Solez – With Remarks on the Banff Meeting Spirit
Bibliographic record
Abstract
The awarding of the gold medal from the Catalan Society of Transplantation to the organizers of the Banff Transplant Pathology meetings is an opportunity to acknowledge gratitude to all the people who have helped make these meetings a success over the past 26 years. Other large organizations have given up consensus conferences, but the Banff consensus process is thriving. It is unusual for any organization to have the same leadership for 26 years. It has only worked for the Banff meetings because the leadership was flexible and able to change with the times. People have often talked about the "special Banff spirit." This year's meeting gave us the opportunity to examine this spirit in detail by analyzing how the meeting consensus sessions and social events functioned. The meeting has never used expert facilitators, but instead has employed experts within the transplant pathology community to moderate discussions. The size of the working sessions is important; they have usually been less than 150 people, which is within "Dunbar's number," meaning that in gatherings of that size one can have empathetic feeling for all the people there. In larger gatherings one loses that "we are all in this together" feeling and people begin thinking "us" versus "them" thoughts. For "unknown" young people the ability to easily talk to well-known leaders in the field is rewarding and keeps them coming back for more time after time. Images of the social events do not suggest any sort of hierarchy; everyone interacts with everyone else.
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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 | 0.010 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.008 | 0.026 |
| Insufficient payload (model declined to judge) | 0.013 | 0.009 |
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".