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Record W192974008 · doi:10.1155/2008/642432

Autoimmune Hepatitis in a North American Aboriginal/First Nations Population

2008· article· en· W192974008 on OpenAlexaffvenueabout
GY Minuk, Shuke Liu, K. Kaita, Siu Ling Wong, Eberhard L. Renner, Julia D. Rempel, Julia Uhanova

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2008
Typearticle
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsMedicineAutoimmune hepatitisCholestasisInternal medicineFibrosisSerologyImmunologyPopulationGastroenterologyHepatitisLiver diseaseAntibody

Abstract

fetched live from OpenAlex

North American Aboriginal populations are at increased risk for developing immune-mediated disorders, including autoimmune hepatitis. In the present study, the demographic, clinical, biochemical, serological, radiological and histological features of autoimmune hepatitis were compared in 33 First Nations (FN) and 150 predominantly Caucasian, non-FN patients referred to an urban tertiary care centre. FN patients were more often female (91% versus 71%; P=0.04), and more likely to have low serum albumin (69% versus 36%; P=0.0006) and elevated bilirubin (57% versus 35%; P=0.01) levels on presentation compared with non-FN patients. They also had lower hemoglobin, and complement levels, more cholestasis and higher serum immunoglobulin A levels than non-FN patients (P=0.05 respectively). Higher histological grades of inflammation and stages of fibrosis, and more clinical and radiological evidence of advanced liver disease were observed in FN patients, but the differences failed to reach statistical significance. The results of the present study suggest that in addition to being more common, autoimmune hepatitis may be more severe in FN populations, compared with predominantly Caucasian, non-FN populations.

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 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)0.000
metaresearch head score (Gemma)0.000
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 score0.703
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.009
GPT teacher head0.235
Teacher spread0.226 · 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 teacher head, 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

Citations38
Published2008
Admission routes3
Has abstractyes

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