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Record W3159322909 · doi:10.1016/j.tige.2021.04.001

The Prevalence of Bile Duct Sludge in Patients With Suspected Bile Duct Stones

2021· article· en· W3159322909 on OpenAlexaff
Rutger Quispel, Lydi M.J.W. van Driel, Marco J. Bruno, Sarto C. Paquin, Anand V. Sahai

Bibliographic record

VenueTechniques and Innovations in Gastrointestinal Endoscopy · 2021
Typearticle
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsMedicineBile ductBiliary sludgeRadiologyCholangiographyCommon bile ductGastroenterologyEndoscopic ultrasonographyEndoscopic ultrasoundInternal medicineGeneral surgeryEndoscopyGallstones

Abstract

fetched live from OpenAlex

Endoscopic Ultrasonography (EUS) in patients with suspected bile duct stones rules out the presence of stones in up to 65% of patients, thus preventing unnecessary Endoscopic Retrograde Cholangiography with Endoscopic Sphincterotomy (ERC with ES) and its complications in the majority of cases.1 Increased use of EUS for ruling out bile duct stones has led to more cases in which bile duct sludge is detected. Sludge is an ultrasound diagnosis usually described as layered, mobile, low-amplitude echoes without shadowing, representing bile precipitate out of solution.

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 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 score0.031
Threshold uncertainty score0.413

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.009
GPT teacher head0.262
Teacher spread0.252 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

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