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Record W7098764505

CMAJ OPEN

2016· article· en· W7098764505 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldChemistry
TopicPlant-Derived Bioactive Compounds
Canadian institutionsnot available
Fundersnot available
KeywordsLiver transplantationHepatitis C virusAsymptomaticLiver diseaseHepatocellular carcinomaPopulationHepatitis CDiseaseChronic liver disease
DOInot available

Abstract

fetched live from OpenAlex

Chronic hepatitis C virus (HCV) infection is a leading cause of cirrhosis, hepatocellular carcinoma and liver transplantation in Canada.1 These complications are expected to increase substantially over the next decade2,3 and cause more years of life lost owing to mortality and subopti-mal health compared with any other infectious disease.4 Canadian guidelines advocate testing for HCV in people with evidence of liver disease or risk factors including injec-tion drug use, receipt of blood products before 1992, and those from endemic countries.5 However, several character-istics of HCV suggest that more widespread screening may be beneficial. First, HCV infection is common. Although the exact prevalence is unknown, at least 250 000 Canadians (0.8 % of the population) are likely infected.2,3 Second, most patients are asymptomatic until advanced liver disease has developed; thus, many patients with HCV are unaware of their HCV infection (21%–70 % in Canada3,6 and 50%–75% in the United States).7 Third, therapies are available that cure the infection in over 80 % of patients,8,9 arrest progres-sion of liver disease and reduce mortality.10 Based on these characteristics, recent US guidelines advocated one-time screening for HCV antibodies in individuals born between Acceptability and yield of birth-cohort screening for hepatitis C virus in a Canadian population being screened for colorectal cancer: a cross-sectional study

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)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.334
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0020.003
Research integrity0.0040.005
Insufficient payload (model declined to judge)0.6660.385

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 head0.032
GPT teacher head0.270
Teacher spread0.237 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2016
Admission routes1
Has abstractyes

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