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Record W2991646690

First Nations hepatitis C virus infections: Six-year retrospective study of on-reserve rates of newly reported infections in northwestern Ontario.

2017· article· en· W2991646690 on OpenAlexaffabout
Janet Gordon, Natalie Bocking, Kathy Pouteau, Terri Farrell, Gareth Ryan, Len Kelly

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsAssembly of First Nations
Fundersnot available
KeywordsMedicineIncidence (geometry)PopulationHepatitis C virusRetrospective cohort studyDemographyHepatitis CDiseasePediatricsEnvironmental healthImmunologyVirusInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVE: To document rates of newly reported hepatitis C virus (HCV) cases from 2010 to 2015 in remote First Nations communities. DESIGN: Retrospective analysis of aggregate data of newly reported HCV antibody-positive (Ab+) cases. SETTING: Northwestern Ontario. PARTICIPANTS: A total of 31 First Nations communities (an on-reserve population of 20 901) supported in health care by the Sioux Lookout First Nations Health Authority. MAIN OUTCOME MEASURES: The aggregate characteristic data included year of notification, age range, and sex for a 6-year period (2010 to 2015). RESULTS: There were 267 HCV Ab+ cases in the 6-year study period. The incidence in 2015 was 324.2 per 100 000 population. This is 11 times the rate for all of Ontario. The most common associated risk factor was sharing of intravenous drug use equipment. Women made up 52% of patients with newly reported HCV Ab+ cases. More than 45% of cases were in patients between 20 and 29 years of age. CONCLUSION: This high burden of newly reported HCV Ab+ cases in geographically remote First Nations communities is concerning, and prevention and treatment resources are needed. This burden of disease might pose more urgent health and social challenges than can be generalized from the experience of the rest of Canada.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.259

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.334
Teacher spread0.268 · 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 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

Citations23
Published2017
Admission routes2
Has abstractyes

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