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Record W2984221112 · doi:10.1016/j.jhep.2019.11.003

Guidance for design and endpoints of clinical trials in chronic hepatitis B - Report from the 2019 EASL-AASLD HBV Treatment Endpoints Conference‡

2019· review· en· W2984221112 on OpenAlexfundno aff
Markus Cornberg, Anna Suk‐Fong Lok, Norah A. Terrault, Fabien Zoulim, Thomas Berg, Maurizia Rossana Brunetto, Stephanie Buchholz, Marı́a Buti, Henry Lik‐Yuen Chan, Kyong‐Mi Chang, Maura Dandri, Geoffrey Dusheiko, Jordan J. Feld, Carlo Ferrari, Marc G. Ghany, Harry L.A. Janssen, Patrick Kennedy, Pietro Lampertico, Jake T. Liang, Stephen Locarnini, Mala K. Maini, Poonam Mishra, George Papatheodoridis, Jörg Petersen, Silke Schlottmann, Su Wang, Heiner Wedemeyer

Bibliographic record

VenueJournal of Hepatology · 2019
Typereview
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsnot available
FundersBarts and The London School of Medicine and DentistryPerelman School of Medicine, University of PennsylvaniaUniversitätsklinikum Hamburg-EppendorfNational Institutes of HealthEuropean Association for the Study of the LiverNational and Kapodistrian University of AthensUniversità degli Studi di ParmaUniversity of TorontoUniversity College LondonNational Institute for Health and Care ResearchUniversitätsklinikum EssenUniversità degli Studi di MilanoUniversity of PennsylvaniaBarts CharityUniversität Duisburg-EssenRocheGilead SciencesDeutsches Zentrum für InfektionsforschungUniversität HamburgBristol-Myers Squibb
KeywordsMedicineHBsAgClinical endpointClinical trialInternal medicineSurrogate endpointHepatitis BDiscontinuationHBeAgChronic hepatitiscccDNAHepatitis B virusGastroenterologyImmunologyVirus

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.136
metaresearch head score (Gemma)0.172
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.864
Threshold uncertainty score0.719

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1360.172
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0150.023
Bibliometrics0.0060.006
Science and technology studies0.0010.002
Scholarly communication0.0090.004
Open science0.0090.004
Research integrity0.0120.016
Insufficient payload (model declined to judge)0.0210.014

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 head0.501
GPT teacher head0.537
Teacher spread0.036 · 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
DomainMethods
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

Citations358
Published2019
Admission routes1
Has abstractno

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