MétaCan
Menu
← Back to cohort
Record W2118968030 · doi:10.1093/cid/cit491

Missed Opportunities for Hepatocellular Carcinoma Screening in an HIV/Hepatitis C Virus-Coinfected Cohort

2013· article· en· W2118968030 on OpenAlexafffund
E Beauchamp, K. Rollet, Sharon Walmsley, David Wong, C. Cooper, Marina B. Klein, Jeffrey Е. Cohen, Barbara R. Conway, Pierre Côté, Joseph Cox, M. John Gill, S. Haider, Marianne Harris, David Haase, Mark Hull, Joan Montaner, EEM Moodie, Neora Pick, A. Rachlis, Danielle Rouleau, Roger Sandre, Marie-Louise Vachon

Bibliographic record

VenueClinical Infectious Diseases · 2013
Typearticle
Languageen
FieldMedicine
TopicHepatitis C virus research
Canadian institutionsOttawa HospitalUniversity of TorontoUniversity Health NetworkRoyal Victoria HospitalMcGill University Health CentreRoyal Victoria Regional Health CentreDéveloppement Economique Longueuil
FundersFonds de Recherche du Québec - SantéCanadian Institutes of Health ResearchUniversité de MontréalCentre Hospitalier Universitaire de QuébecMcGill UniversityUniversity of OttawaMcMaster UniversityStyrelsen för Internationellt Utvecklingssamarbete
KeywordsMedicineHepatocellular carcinomaCohortHepatitis C virusCirrhosisHuman immunodeficiency virus (HIV)Internal medicineHepatitis CCohort studyUltrasoundVirologyGastroenterologyVirusRadiology

Abstract

fetched live from OpenAlex

We examined adherence to guidelines for screening of hepatocellular carcinoma in a cohort of HIV/hepatitis C virus-coinfected patients. Thirty-six percent of patients with documented cirrhosis did not have a screening ultrasound. Patients at centers with standardized systems for screening were more likely to have had an ultrasound performed.

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)0.005
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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.167
GPT teacher head0.389
Teacher spread0.221 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

Explore more

Same venueClinical Infectious Diseases→Same topicHepatitis C virus research→French-language works237,207→