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Record W1542725669 · doi:10.1155/2012/176543

Alagille Syndrome and Wilson Disease in Siblings: A Diagnostic Conundrum

2012· article· en· W1542725669 on OpenAlexaffvenue
Meghan Amson, Esther Lamoureux, Nir Hilzenrat, Marc Tischkowitz

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2012
Typearticle
Languageen
FieldMedicine
TopicPediatric Hepatobiliary Diseases and Treatments
Canadian institutionsMcGill UniversityJewish General Hospital
Fundersnot available
KeywordsAlagille syndromeWilson's diseaseCholestasisAsymptomaticMedicineLiver diseaseDiseaseProgressive familial intrahepatic cholestasisLiver function testsGenetic testingContext (archaeology)GastroenterologyPathologyInternal medicineLiver transplantationBiology

Abstract

fetched live from OpenAlex

The authors describe two siblings, each with a different, rare genetic condition that affects liver function. The index case, the 18-year-old asymptomatic brother of a young man recently diagnosed with Wilson disease, presented for Wilson disease screening and was also found to have abnormal liver function suggestive of cholestasis. However, ceruloplasmin level, 24 h urine copper concentration and liver synthetic function were normal. Further hepatic investigations and genetic mutation analysis were performed, ultimately leading to a diagnosis of Alagille syndrome. He was treated with ursodiol, which resulted in normalization of his liver function tests. Subsequently, he was found to be a carrier for a mutation in the Wilson disease gene, ATP7B. In the present report, the potential implications of being a heterozygote for Wilson disease in the context of Alagille syndrome are discussed. Also stressed is that care must be exercised by the clinician when diagnosing family members who may present with two different disorders closely mimicking one another.

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)0.010
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 score0.005
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.010
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.003
Scholarly communication0.0020.003
Open science0.0010.003
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.0040.001

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 head0.231
Teacher spread0.222 · 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

Citations3
Published2012
Admission routes2
Has abstractyes

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