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Record W4404353201 · doi:10.1097/hc9.0000000000000590

Management of primary sclerosing cholangitis: Current state-of-the-art

2024· review· en· W4404353201 on OpenAlexaff
Guilherme Grossi Lopes Cançado, Gideon M. Hirschfield

Bibliographic record

VenueHepatology Communications · 2024
Typereview
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsToronto General HospitalUniversity Health Network
Fundersnot available
KeywordsPrimary sclerosing cholangitisMedicineDiseaseInflammatory bowel diseaseIntensive care medicineLiver transplantationPsychological interventionIntervention (counseling)Liver diseaseClinical trialTransplantationInternal medicine

Abstract

fetched live from OpenAlex

Primary sclerosing cholangitis is a chronic liver disease characterized by progressive inflammation and fibrosis of medium-large bile ducts, most commonly in association with inflammatory bowel disease. Most patients have a progressive disease course, alongside a heightened risk of hepatobiliary and colorectal cancer. Medical therapies are lacking, and this, in part, reflects a poor grasp of disease biology. As a result, current management is largely supportive, with liver transplantation an effective life-prolonging intervention when needed, but not one that cures disease. Emerging therapies targeting disease progression, as well as symptoms such as pruritus, continue to be explored. The trial design is increasingly cognizant of the application of thoughtful inclusion criteria, as well as better endpoints aimed at using surrogates of disease that can identify treatment benefits early. This is hoped to facilitate much-needed advances toward developing safe and effective interventions for patients.

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)0.002
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.002

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 head0.132
GPT teacher head0.391
Teacher spread0.259 · 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
GenreReview

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

Citations10
Published2024
Admission routes1
Has abstractyes

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