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Record W2974241762 · doi:10.1016/j.jaut.2019.102328

The challenges of primary biliary cholangitis: What is new and what needs to be done

2019· review· en· W2974241762 on OpenAlexaff
Benedetta Terziroli Beretta‐Piccoli, Giorgina Mieli‐Vergani, Diego Vergani, John M. Vierling, David Adams, Gianfranco Alpini, Jesús M. Bañales, Ulrich Beuers, Einar S. Björnsson, Christopher L. Bowlus, Marco Carbone, Olivier Chazouillères, George Ν. Dalekos, Andrea De Gottardi, Kenichi Harada, Gideon M. Hirschfield, Pietro Invernizzi, David Jones, Edward L. Krawitt, Antonio Lanzavecchia, Zhe‐Xiong Lian, Xiong Ma, Michael P. Manns, Domenico Mavilio, Eamon MM. Quigley, Federica Sallusto, Shinji Shimoda, Mario Strazzabosco, Mark G. Swain, Atsushi Tanaka, Michael Trauner, Koichi Tsuneyama, Ehud Zigmond, M. Eric Gershwin

Bibliographic record

VenueJournal of Autoimmunity · 2019
Typereview
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsUniversity of TorontoUniversity Health NetworkUniversity of CalgaryToronto Liver Centre
FundersMedical Research CouncilNational Institute for Health and Care Research
KeywordsObeticholic acidUrsodeoxycholic acidPrimary biliary cirrhosisCholestasisMedicineBile acidGastroenterologyAutoantibodyInternal medicineLiver diseasePathologyAntibodyImmunology

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)0.003
metaresearch head score (Gemma)0.004
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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0040.005
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.092
GPT teacher head0.332
Teacher spread0.240 · 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

Citations115
Published2019
Admission routes1
Has abstractno

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