Chronic gvhd dictionary—eurograft cost action initiative consensus report
Bibliographic record
Abstract
Chronic graft versus host disease (cGVHD) affects patients after allogeneic hematopoietic stem cell transplantation (alloHSCT). This orphan disease poses a challenge for clinicians and researchers. The purpose of the cGVHD Dictionary is to provide a standardized structure for cGVHD databases on an international level, reconciling differences in data retrieval and facilitate database merging. It is derived from several consensus meetings of the EUROGRAFT consortium (European Cooperation in Science and Technology-COST Action CA17138) followed by a consensus process involving European Society for Blood and Marrow Transplantation (EBMT), US GvHD consortium and Center for International Bone Marrow Transplant Registry (CIBMTR). Databases used for the dictionary were: the National Institutes of Health (NIH) database, the Center for International Blood and Marrow Transplant Research, Applying Biomarkers to Minimize Long Term Effects of Childhood/Adolescent Cancer Treatment - Pediatric Blood and Marrow Transplant Consortium database, EBMT registry, the German-Austrian-Swiss GvHD registry, Italian Blood and Marrow Transplantation Society registry and Regensburg-Göttingen-Newcastle HSCT dataset. A four-part cGVHD Dictionary was formed based on the databases, consensus, and evidence in the literature. The Dictionary is divided into: (1) Patient characteristics, (2) Transplant characteristics, (3) cGVHD characteristics and (4) patient-reported quality of life, symptom burden and functional indicators.
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 | 0.028 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.012 | 0.015 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 0.007 |
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".