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Record W4389346648 · doi:10.1016/j.jtct.2023.11.019

Genetic Findings of Potential Donor Origin following Hematopoietic Cell Transplantation: Recommendations on Donor Disclosure and Genetic Testing from the World Marrow Donor Association

2023· article· en· W4389346648 on OpenAlexaff
Angharad Pryce, Eefke van Eerden, Meghann Cody, Jason Oakes, Anna M. DeSalvo, Sarah Bannon, Catherine Burlton, Rachel Pawson, Warren Fingrut, Francisco M. Barriga, Jane L. Ward, Charlotte Ingram, Michael F. Walsh, Khaled El‐Ghariani, Sunday Ocheni, Laura Machin, David Allan, Thilo Mengling, Chloe Anthias

Bibliographic record

VenueTransplantation and Cellular Therapy · 2023
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsCanadian Blood Services
Fundersnot available
KeywordsTransplantationHematopoietic cellMedicineDiseaseGenetic testingHematopoietic stem cell transplantationTransplantation ChimeraHaematopoiesisIntensive care medicineBioinformaticsStem cellInternal medicineGeneticsBiology

Abstract

fetched live from OpenAlex

Following hematopoietic cell transplantation (HCT), recipients are subjected to extensive genetic testing to monitor the efficacy of the transplantation and identify relapsing malignant disease. This testing is increasingly including the use of large gene panels, which may lead to incidental identification of genetic and molecular information of potential donor origin. Deciphering whether variants are of donor origin, and if so, whether there are clinical implications for the donor can prove challenging. In response to queries from donor registries and transplant centers regarding best practices in managing donors when genetic mutations of potential donor origin are identified, the Medical Working Group of the World Marrow Donor Association established an expert group to review available evidence and develop a framework to aid decision making. These guidelines aim to provide recommendations on predonation consenting, postdonation testing of recipients, and informing and managing donors when findings of potential donor origin are identified in recipients post-transplantation. It is recognized that registries will have different access to resources and financing structures, and thus whenever possible, we have made suggestions on how recommendations can be adapted.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.024
GPT teacher head0.259
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2023
Admission routes1
Has abstractyes

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