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Record W4400103955 · doi:10.14740/jh1257

A Unique Case of a Compound Heterozygosity of Hemoglobin Korle-Bu and Sickle Cell Trait in a Military Trainee

2024· article· en· W4400103955 on OpenAlexvenueno aff
Gartrell C. Bowling, Niels A. Ryden, Allen R. Holmes, Lauren E. Lee, Kristin Stoll

Bibliographic record

VenueJournal of Hematology · 2024
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsnot available
FundersUniformed Services University of the Health SciencesU.S. Department of Defense
KeywordsCompound heterozygositySickle cell traitLoss of heterozygosityHemoglobinAsymptomaticMedicinePhenotypeHemoglobin sMolecular biologyHemoglobinopathyGeneticsGenePathologyBiologyImmunologyHemolytic anemiaSickle cell anemiaInternal medicineAlleleDisease

Abstract

fetched live from OpenAlex

Hemoglobin Korle-Bu (Hb KB) is a rare and likely under-reported hemoglobin (Hb) variant resulting from an unusual point mutation on the beta-globin chain. Hb KB is typically clinically silent, and there are limited reports of Hb KB heterozygosity compounded with other hemoglobinopathies that can present with varying clinical phenotypes. Here, we report a case of compound Hb KB heterozygosity with Hb S in an asymptomatic military trainee with a positive sickle cell screening test. Hb capillary and gel electrophoresis predicted a compound Hb S/D-Punjab overlap, which foretells a severe clinical phenotype. Sequencing of the Hb beta gene HBB demonstrated Hb KB, allowing for a diagnosis that fit his asymptomatic clinical phenotype and allowed for retention in the military. J Hematol. 2024;13(3):116-120 doi: https://doi.org/10.14740/jh1257

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.259
Teacher spread0.250 · 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 designCase report
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
Published2024
Admission routes1
Has abstractyes

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