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Record W4242042519 · doi:10.1016/j.bbmt.2011.12.070

Late Effects in Hematopoietic Cell Transplant Recipients with Acquired Severe Aplastic Anemia: A Report from the Late Effects Working Committee of the Center for International Blood and Marrow Transplant Research (CIBMTR)

2012· article· en· W4242042519 on OpenAlexaff
Dave Buchbinder, Diane J. Nugent, Ruta Brazauskas, ZiXuan Wang, Mahmoud Aljurf, Mitchell S. Cairo, R. Chow, C.N. Duncan, Lamis Eldjerou, V. Gupta, Gregory A. Hale, Jörg Halter, Brandon Hayes‐Lattin, J Hsu, David A. Jacobsohn, R T Kamble, Kimberly A. Kasow, Hillard M. Lazarus, Pramod P. Mehta, Kurt Myers, Susan K. Parsons, Jakob Passweg, Joseph Pidala, V. Reddy, C.M. Sales-Bonfim, Bipin N. Savani, Adriana Seber, Mohamed L. Sorror, Amir Steinberg, William A. Wood, David A. Wall, Jacek Winiarski, L.C. Yu, Navneet S. Majhail

Bibliographic record

VenueBiology of Blood and Marrow Transplantation · 2012
Typearticle
Languageen
FieldMedicine
TopicHematopoietic Stem Cell Transplantation
Canadian institutionsUniversity of ManitobaCancerCare ManitobaPrincess Margaret Cancer Centre
Fundersnot available
KeywordsMedicineAplastic anemiaHematopoietic cellTransplantationInternal medicineRegimenPopulationSingle CenterAnemiaSurgeryGastroenterologyBone marrowHaematopoiesisStem cell

Abstract

fetched live from OpenAlex

With improvements in hematopoietic cell transplantation (HCT) for severe aplastic anemia (SAA), there is a growing population of SAA survivors of HCT. However, there is a paucity of information regarding late effects in SAA HCT survivors. We analyzed the burden of malignant and non-malignant late effects in HCT survivors with acquired SAA.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2012
Admission routes1
Has abstractyes

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