History of the Banff classification of allograft pathology as it approaches its 20th year
Bibliographic record
Abstract
PURPOSE OF REVIEW: To revisit the history and main defining characteristics of the Banff classification. RECENT FINDINGS: From small beginnings in 1991 the Banff classification of renal allograft pathology has grown to be the major standard setting force in renal transplant pathology and in international clinical trials of new antirejection agents. The meeting and classification has unique history, consensus generation mechanisms, funding, and tradition, and looks poised to continue for at least another 20 years. The Banff meetings also deal with setting standards for most other areas of solid organ transplantation and increasingly incorporate training courses and working groups so the activity never stops. SUMMARY: The Banff meeting has gone from being just another meeting to becoming the embodiment of the global standard, The Banff Classification, by which we determine the presence of rejection and other important disease conditions in the transplanted organ. It is crucial for patient care and crucial for clinical trials of new therapies that it remains updated and modern, an important dynamic yardstick against which we measure clinical success.
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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 | 0.007 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.003 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".