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Record W4377011635 · doi:10.1097/hep.0000000000000465

Letter to the Editor: People living with HIV and NAFLD—A population left behind in the global effort for liver fibrosis screening?

2023· letter· en· W4377011635 on OpenAlexaff
Giada Sebastiani, Jovana Milić, Emmanuel Tsochatzis, Catia Marzolini, Michael Betel, Sanjay Bhagani, Caryn G. Morse, Felice Cinque, James Maurice, Patrick Ingiliz, Jennifer C. Price, Maud Lemoine, Jürgen K. Rockstroh, Giovanni Guaraldi

Bibliographic record

VenueHepatology · 2023
Typeletter
Languageen
FieldMedicine
TopicLiver Disease Diagnosis and Treatment
Canadian institutionsMcGill University Health Centre
Fundersnot available
KeywordsHuman immunodeficiency virus (HIV)Liver fibrosisMedicinePopulationFibrosisLetter to the editorGerontologyInternal medicineFamily medicineEnvironmental healthPolitical scienceLaw

Abstract

fetched live from OpenAlex

fibrosis.We believe that their inclusion into guidelines will also help address current gaps in the pathogenesis and natural history of HIV-associated NASH.Moreover, PWH are currently excluded from the global effort of therapeutic trials for nonalcoholic steatohepatitis (NASH)(2).The endorsement of the hepatological community is crucial in promoting awareness, research and public health efforts among stakeholders in HIV medicine.

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)0.002
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.018
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0180.015
Insufficient payload (model declined to judge)0.0060.005

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 head0.015
GPT teacher head0.259
Teacher spread0.245 · 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 designNot applicable
Domainnot available
GenreCommentary

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
Published2023
Admission routes1
Has abstractyes

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