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Record W4408266863 · doi:10.1016/j.dld.2025.01.016

Real-world practice patterns on the use of terlipressin in patients with cirrhosis and acute kidney injury - results from the ICA-GLOBAL AKI study

2025· article· en· W4408266863 on OpenAlexaff
Simone Incicco, Ann T., Adrià Juanola, Kavish R. Patidar, Anna Barone, Anand J. Kulkarni, J.L. Pérez-Hernández, B. C. Wentworth, Sumeet K. Asrani, Carlo Alessandria, Nadia Abdelaaty Abdelkader, Yu Jun Wong, Qing Xie, Nikolaos Pyrsopoulos, S.E. Kim, Yasser Fouad, Aldo Torre, E. Cerda Reyes, Javier Díaz‐Ferrer, Rakhi Maiwall, Douglas A. Simonetto, Mária Papp, Eric S. Orman, Giovanni Perricone, Cristina Solé, Christian M. Lange, Alberto Queiróz Farias, G. Pereira, Adrián Gadano, Paolo Caraceni, Thierry Thévenot, Nipun Verma, J.H. Kim, Julio Vorobioff, Jacqueline Córdova‐Gallardo, В. Т. Ивашкин, Juan Pablo Roblero, Raoel Maan, Claudio Toledo, O. Riggio, E Fassio, Mónica Marino, Puria Nabilou, Víctor Manuel Vargas, M. Merli, L. L. Goncalves, Liane Rabinowich, Aleksander Krag, Lorenz Balcar, Pedro Montes, Ângelo Zambam de Mattos, Tony Bruns, Abdulsemed Mohammed Nur, Wim Laleman, Enrique Carrera Estupiñán, M.C. Cabrera, Marcos Girala, Hrishikesh Samant, Sarah Raevens, João Madaleno, W. Ray Kim, Juan Pablo Arab, José Presa, Carlos Noronha Ferreira, A Galante, Olivier Roux, Andrew S. Allegretti, R. Bart Takkenberg, Sebastián Marciano, S. K. Sarin, Pere Ginès, P. Angeli, E. Solà, S. Piano

Bibliographic record

VenueDigestive and Liver Disease · 2025
Typearticle
Languageen
FieldMedicine
TopicElectrolyte and hormonal disorders
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsTerlipressinMedicineAcute kidney injuryCirrhosisInternal medicineIntensive care medicineHepatorenal syndrome

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.766

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.015
GPT teacher head0.278
Teacher spread0.263 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations1
Published2025
Admission routes1
Has abstractno

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