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Record W2527848138 · doi:10.1136/gutjnl-2016-312288

Management of <i>Helicobacter pylori</i> infection—the Maastricht V/Florence Consensus Report

2016· article· en· W2527848138 on OpenAlexaff
Peter Malfertheiner, Françis Mégraud, Colm O’Morain, Javier P. Gisbert, Ernst J. Kuipers, Anthony Axon, Franco Bazzoli, Antonio Gasbarrini, J. Atherton, David Y. Graham, Richard H. Hunt, Paul Moayyedi, Theodore Rokkas, Massimo Rugge, Michael Selgrad, Sebastian Suerbaum, Kentaro Sugano, Emad El‐Omar

Bibliographic record

VenueGut · 2016
Typearticle
Languageen
FieldMedicine
TopicHelicobacter pylori-related gastroenterology studies
Canadian institutionsMcMaster University
FundersNational Institute of Diabetes and Digestive and Kidney Diseases
KeywordsHelicobacter pyloriHelicobacter InfectionsMedicineConsensus conferenceGastroenterologyHelicobacter pylori infectionInternal medicine

Abstract

fetched live from OpenAlex

Important progress has been made in the management of Helicobacter pylori infection and in this fifth edition of the Maastricht Consensus Report, key aspects related to the clinical role of H. pylori were re-evaluated in 2015. In the Maastricht V/Florence Consensus Conference, 43 experts from 24 countries examined new data related to H. pylori in five subdivided workshops: (1) Indications/Associations, (2) Diagnosis, (3) Treatment, (4) Prevention/Public Health, (5) H. pylori and the Gastric Microbiota. The results of the individual workshops were presented to a final consensus voting that included all participants. Recommendations are provided on the basis of the best available evidence and relevance to the management of H. pylori infection in the various clinical scenarios.

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)0.038
metaresearch head score (Gemma)0.053
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: Review · Consensus signal: Review
Teacher disagreement score0.038
Threshold uncertainty score0.203

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0380.053
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0040.002
Science and technology studies0.0010.002
Scholarly communication0.0040.003
Open science0.0050.005
Research integrity0.0060.004
Insufficient payload (model declined to judge)0.0030.002

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 head0.020
GPT teacher head0.266
Teacher spread0.246 · 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

Citations2,924
Published2016
Admission routes1
Has abstractyes

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