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Record W1071546559 · doi:10.1053/j.gastro.2015.07.061

Development and Validation of a Scoring System to Predict Outcomes of Patients With Primary Biliary Cirrhosis Receiving Ursodeoxycholic Acid Therapy

2015· review· en· W1071546559 on OpenAlexafffund
Willem J. Lammers, Gideon M. Hirschfield, Christophe Corpechot, Frederik Nevens, Keith D. Lindor, Harry L.A. Janssen, Annarosa Floreani, Cyriel Y. Ponsioen, Marlyn J. Mayo, Pietro Invernizzi, Pier Maria Battezzati, Albert Parés, Andrew K. Burroughs, Andrew L. Mason, Kris V. Kowdley, Teru Kumagi, Maren H. Harms, Palak Trivedi, Raoul Poupon, Angela Cheung, Ana Lleò, Llorenç Caballería, Bettina E. Hansen, Henk R. van Buuren

Bibliographic record

VenueGastroenterology · 2015
Typereview
Languageen
FieldMedicine
TopicLiver Diseases and Immunity
Canadian institutionsUniversity of AlbertaUniversity Health Network
FundersNovartisInnogeneticsAlberta Cancer FoundationCanadian Institutes of Health ResearchIntercept PharmaceuticalsMeso Scale DiagnosticsMedical Research CouncilAlberta Heritage Foundation for Medical ResearchFerring PharmaceuticalsCanadian Liver FoundationIkariaJanssen PharmaceuticalsGilead SciencesCilagMedtronicTakeda Pharmaceutical CompanyAbbVieAbbott LaboratoriesMerckGlaxoSmithKlineStichting voor Lever- en Maag-Darm OnderzoekWellcome TrustRocheAstellas Pharma US
KeywordsMedicineHazard ratioUrsodeoxycholic acidInternal medicineConfidence intervalLiver transplantationPrimary biliary cirrhosisGastroenterologyProportional hazards modelTransplantationCohortPopulation

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)0.004
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0020.001
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 head0.037
GPT teacher head0.285
Teacher spread0.248 · 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
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

Citations436
Published2015
Admission routes2
Has abstractno

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