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Record W4200157423 · doi:10.3138/canlivj-2021-0032

Barriers to hepatitis C diagnosis and treatment in the DAA era: Preliminary results of a community-based survey of primary care practitioners

2021· article· en· W4200157423 on OpenAlexaffvenueabout
Sanjeev Sirpal, Natasha Chandok

Bibliographic record

VenueCanadian Liver Journal · 2021
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsBrampton Civic HospitalCentre Intégré Universitaire de Santé et de Services Sociaux du Centre-Sud-de-l'Île-de-Montréal
Fundersnot available
KeywordsContext (archaeology)BattlePandemicPublic healthMedicineHealth carePrimary careFamily medicineNursingPolitical scienceCoronavirus disease 2019 (COVID-19)GeographyDiseaseInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

Notwithstanding the groundbreaking achievement of hepatitis C curative treatment with direct-acting antiviral therapies, Canada faces an uphill battle in reaching the 2030 goal of viral elimination set forth by the World Health Organization, a goal made more difficult by the COVID-19 pandemic. There is limited understanding of the diagnostic and treatment barriers, and challenges in linkage to care in Canada, especially as it pertains to primary care providers in a community context. Therefore, in this article, the authors conducted a survey study to evaluate the following factors: primary care providers' knowledge of specialist treatment options and the importance of screening and treatment; and patient factors, including transportation, linguistic barriers, and other socio-economic status indicators that impact the screening and management of hepatitis C. The results suggest that public health campaigns that protocolize and/or incentivize screening and referrals may provide solutions to addressing such barriers.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.219
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.067
GPT teacher head0.314
Teacher spread0.248 · 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

Citations2
Published2021
Admission routes3
Has abstractyes

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