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Record W2978585643 · doi:10.14740/gr1206

Diagnosis and Treatment of Genetic <i>HFE</i>-Hemochromatosis: The Danish Aspect

2019· review· en· W2978585643 on OpenAlexvenueno aff
Nils Milman, Frank Vinholt Schioedt, Anders Junker, Karin Magnussen

Bibliographic record

VenueGastroenterology Research · 2019
Typereview
Languageen
FieldMedicine
TopicIron Metabolism and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsDanishHemochromatosisMedicineHereditary hemochromatosisGeneticsInternal medicineBiology

Abstract

fetched live from OpenAlex

This paper outlines the Danish aspects of HFE -hemochromatosis, which is the most frequent genetic predisposition to iron overload in the five million ethnic Danes; more than 20,000 people are homozygous for the C282Y mutation and more than 500,000 people are compound heterozygous or heterozygous for the HFE -mutations. The disorder has a long preclinical stage with gradually increasing body iron overload and eventually 30% of men will develop clinically overt disease, presenting with symptoms of fatigue, arthralgias, reduced libido, erectile dysfunction, cardiac disease and diabetes. Subsequently the disease may progress into irreversible arthritis, liver cirrhosis, cardiomyopathy, pancreatic fibrosis and osteoporosis. The effective standard treatment is repeated phlebotomies, which in the preclinical and early clinical stages ensures a normal survival rate. Early detection of the genetic predisposition to the disorder is therefore important to reduce the overall burden of clinical disease. Population screening seems to be cost-effective and should be considered. Gastroenterol Res. 2019;12(5):221-232 doi: https://doi.org/10.14740/gr1206

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.127
GPT teacher head0.409
Teacher spread0.282 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations39
Published2019
Admission routes1
Has abstractyes

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