Pathologic Evaluation of Pig Kidney and Heart Xenografts: 2024 Recommendations from the Banff Xenotransplantation Pathology Working Group
Bibliographic record
Abstract
The purpose of this white paper is to recommend the minimum reporting standards for pathologic characterization of kidney and heart xenografts in humans. This proposal is based on the current human classifications for kidney and heart allografts, with additions and caveats relevant to xenografts that are primarily based on non-human primate and a limited number of organ xenografts in decedent and living humans. Such recommendations should not be regarded as diagnostic criteria, given that many new pathologic patterns and mechanisms remain to be fully characterized. While xenograft transplantation continues to evolve, this report serves as groundwork and an initial step towards defining international standards in xenograft histopathology assessment and reporting. Note: The authors welcome comments from the international transplantation community through the AJT Banff Blog: https://amjtransplant.wixsite.com/ajtbanffblog
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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 | 0.098 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.005 | 0.003 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 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".