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Record W1995906997 · doi:10.1016/j.bbmt.2008.01.005

Chronic Graft-versus-Host Disease—Implementation of the National Institutes of Health Consensus Criteria for Clinical Trials

2008· article· en· W1995906997 on OpenAlexaff
Linda M. Griffith, Steven Z. Pavletic, Stephanie J. Lee, Paul J. Martin, Kirk R. Schultz, Georgia B. Vogelsang

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2008
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsUniversity of British Columbia
FundersNational Institute of Allergy and Infectious DiseasesNational Cancer InstituteNational Institutes of Health
KeywordsMedicineGraft-versus-host diseaseClinical trialScopusDiseaseHematopoietic cellInternal medicineMEDLINEHaematopoiesisStem cell

Abstract

fetched live from OpenAlex

Based on collaborative discussions of the community of hematopoietic cell transplant (HCT) physicians, the National Institutes of Health (NIH) Consensus Criteria for Clinical Trials in Chronic Graft-versus-Host Disease (GVHD) established for the first time comprehensive diagnostic, staging, and response criteria for chronic GVHD (cGVHD). The recommendations from this group were published in a series of articles in this journal [1-6]. Implementation of the criteria and follow-up research are needed to ensure continued progress.

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 imitation

Not 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.

metaresearch head score (Codex)0.566
metaresearch head score (Gemma)0.484
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.566
Threshold uncertainty score0.536

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.5660.484
Meta-epidemiology (narrow)0.0040.004
Meta-epidemiology (broad)0.0140.013
Bibliometrics0.0090.012
Science and technology studies0.0080.011
Scholarly communication0.0200.008
Open science0.0210.011
Research integrity0.0260.033
Insufficient payload (model declined to judge)0.0040.004

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.

Opus teacher head0.204
GPT teacher head0.462
Teacher spread0.258 · 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 source (direct Gemma or distilled Codex), 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

Citations20
Published2008
Admission routes1
Has abstractyes

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