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Record W1515048280 · doi:10.4254/wjh.v7.i9.1265

Hepatitis B among Inuit: A review with focus on Greenland Inuit

2015· review· en· W1515048280 on OpenAlexaboutno aff
Karsten Fleischer Rex

Bibliographic record

VenueWorld Journal of Hepatology · 2015
Typereview
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineHepatocellular carcinomaHepatitis B virusEpidemiologyCirrhosisHepatitis BLiver diseaseDiseaseLiver cancerPopulationChronic liver diseaseSerologyImmunologyEnvironmental healthVirologyDemographyInternal medicineVirusAntibody

Abstract

fetched live from OpenAlex

Hepatitis B virus (HBV) infection is a disease with a highly variable course. Chronic HBV infection may cause end-stage liver disease including cirrhosis and hepatocellular carcinoma, which is the 3(rd) most common cause of cancer related death due to the poor prognosis. The prevalence of HBV infection is low in many countries. Still, it remains important due to the potential consequences of the disease. HBV is endemic in the Arctic with serologic markers of chronic HBV infection in up to 29% of the population in some areas in Greenland. Interestingly, Inuit populations rarely show signs of liver disease despite the fact that around half of all Inuit has been exposed to HBV and around 8% of Inuit are chronically infected with HBV. These findings have been consistent in surveys conducted for more than four decades among Arctic Inuit. We thus review HBV infection in the Arctic with focus on Greenland Inuit and compared with Inuit in Canada, Alaska and Siberia. The aspects described include epidemiology and monitoring of the disease, as well as treatment and the risk of liver cancer.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.004
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.050
GPT teacher head0.343
Teacher spread0.293 · 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 designSystematic review
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

Citations35
Published2015
Admission routes1
Has abstractyes

Explore more

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