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Record W4399718312 · doi:10.1093/ecco-jcc/jjae089

ECCO Guidelines on Therapeutics in Crohn’s Disease: Surgical Treatment

2024· article· en· W4399718312 on OpenAlexaff
Michel Adamina, Silvia Minozzi, Janindra Warusavitarne, Christianne J. Buskens, María Chaparro, Bram Verstockt, Uri Kopylov, Henit Yanai, Stephan R. Vavricka, Rotem Sigall Boneh, Giuseppe Sica, Cathérine Reenaers, Georgios Peros, Konstantinos Papamichael, Nurulamin M Noor, Gordon W. Moran, Christian Maaser, Gaetano Luglio, Paulo Gustavo Kotze, Taku Kobayashi, Konstantinos Κarmiris, Christina Kapizioni, Nusrat Iqbal, Marietta Iacucci, Stefan D. Holubar, Jurij Hanžel, João Sabino, Javier P. Gisbert, Gionata Fiorino, Catarina Fidalgo, Pierre Ellu, Alaa El‐Hussuna, Joline de Groof, Wladyslawa Czuber‐Dochan, María José Casanova, Johan Burisch, Steven R. Brown, Gabriele Bislenghi, Dominik Bettenworth, Robert Battat, Raja Atreya, Mariangela Allocca, Manasi Agrawal, Tim Raine, Hannah Gordon, Pär Myrelid

Bibliographic record

VenueJournal of Crohn s and Colitis · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicInflammatory Bowel Disease
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineCrohn's diseaseDiseaseGeneral surgeryIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

This article is the second in a series of two publications on the European Crohn's and Colitis Organisation [ECCO] evidence-based consensus on the management of Crohn's disease. The first article covers medical management; the present article addresses surgical management, including preoperative aspects and drug management before surgery. It also provides technical advice for a variety of common clinical situations. Both articles together represent the evidence-based recommendations of the ECCO for Crohn's disease and an update of prior ECCO Guidelines.

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)0.008
metaresearch head score (Gemma)0.022
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: Not applicable
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.004
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0030.003
Research integrity0.0070.007
Insufficient payload (model declined to judge)0.0070.005

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 head0.022
GPT teacher head0.310
Teacher spread0.288 · 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
GenreMethods

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

Citations145
Published2024
Admission routes1
Has abstractyes

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