Banff 2011 Meeting Report: New Concepts in Antibody-Mediated Rejection
Bibliographic record
Abstract
The 11th Banff meeting was held in Paris, France, from June 5 to 10, 2011, with a focus on refining diagnostic criteria for antibody-mediated rejection (ABMR). The major outcome was the acknowledgment of C4d-negative ABMR in kidney transplants. Diagnostic criteria for ABMR have also been revisited in other types of transplants. It was recognized that ABMR is associated with heterogeneous phenotypes even within the same type of transplant. This highlights the necessity of further refining the respective diagnostic criteria, and is of particular significance for the design of randomized clinical trials. A reliable phenotyping will allow for definition of robust end-points. To address this unmet need and to allow for an evidence-based refinement of the Banff classification, Banff Working Groups presented multicenter data regarding the reproducibility of features relevant to the diagnosis of ABMR. However, the consensus was that more data are necessary and further Banff Working Group activities were initiated. A new Banff working group was created to define diagnostic criteria for ABMR in kidneys independent of C4d. Results are expected to be presented at the 12th Banff meeting to be held in 2013 in Brazil. No change to the Banff classification occurred in 2011.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.010 | 0.008 |
| Insufficient payload (model declined to judge) | 0.012 | 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".