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Record W261073439 · doi:10.24095/hpcdp.33.3.04

Evolution of the determinants of chronic liver disease in Quebec

2013· article· en· W261073439 on OpenAlexaffvenueabout
AJ Sanabria, Réjean Dion, Enriqueta Lucar, JC Soto

Bibliographic record

VenueChronic diseases and injuries in Canada · 2013
Typearticle
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsMcGill UniversitySte. Anne's HospitalInstitut National de Santé Publique du Québec
Fundersnot available
KeywordsMedicineIncidence (geometry)ObesityAlcohol consumptionHepatitis BLiver cancerPublic healthChronic liver diseaseDemographyViral hepatitisChronic hepatitisGynecologyGerontologyCancerInternal medicineAlcoholImmunologyCirrhosisVirus

Abstract

fetched live from OpenAlex

INTRODUCTION: Chronic liver diseases (CLDs) are a worldwide problem. Morbidity and mortality due to CLDs could be avoided or reduced by targeting the main risk factors, including obesity and alcohol use. METHODS: To describe the evolution of the key determinants of CLDs in Quebec, we studied the trends in obesity, alcohol use, viral hepatitis B and C, CLD mortality and hospitalization rates, and the liver cancer incidence rate between January 1, 1981, and December 31, 2009. RESULTS: We observed an increase in the obesity indicators among young men and in alcohol use among adolescent girls and middle-aged women. The overall hepatitis B and C incidence and CLD mortality rates are falling. However, liver cancer and mortality rates, especially among men and the elderly, are on the rise. CONCLUSION: These results highlight the importance of targeted public health interventions and of maintaining or improving access to care for CLDs.

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)0.002
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 score0.031
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.005
GPT teacher head0.217
Teacher spread0.213 · 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

Citations2
Published2013
Admission routes3
Has abstractyes

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