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Record W4406122225 · doi:10.1016/j.gimo.2024.101959

Association of HFE genotypes with hemochromatosis-related phenotypes in the All of Us research program

2025· article· en· W4406122225 on OpenAlex
Nandana D. Rao, Ramal Moonesinghe, Paul C. Adams, Gail P. Jarvik, Kris V. Kowdley, Laura A. Schieve, Scott D. Grosse, W. David Dotson, Muin J. Khoury

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueGenetics in Medicine Open · 2025
Typearticle
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsWestern University
FundersOak Ridge Institute for Science and EducationCenters for Disease Control and PreventionNational Institutes of HealthProtagonist TherapeuticsU.S. Department of Energy
KeywordsHemochromatosisPhenotypeGenotypeHereditary hemochromatosisAssociation (psychology)GeneticsMedicineBiologyPsychologyGene

Abstract

fetched live from OpenAlex

Purpose: variation with HH-related phenotypes and assess the prevalence of testing and diagnosis of HH using All of Us data. Methods: genotypes, we examined the prevalence of HH diagnosis codes and related biochemical and clinical phenotypes. Results: = .0001). Of the 71 participants who were p.Cys282Tyr homozygotes with indication of liver disease, 32 (45.1%) did not have a serum transferrin-iron saturation measure, and 37 (52.1%) did not have diagnosis codes for HH. Conclusion: Limited serum transferrin-iron saturation measures or HH diagnosis codes among p.Cys282Tyr homozygotes, even those with liver disease, suggests potential undertesting and underdiagnosis of type 1 HH in clinical practice and a need for improved awareness, education, and testing around HH.

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.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.053
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.042
GPT teacher head0.409
Teacher spread0.367 · 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