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Record W2159228699 · doi:10.1155/2012/435050

A Novel Two-Step Approach for Retrieval of an Impacted Biliary Extraction Basket

2012· article· en· W2159228699 on OpenAlexaff
Calvin Chan, Fergal Donnellan, Godfrey C. K. Chan, Michael F. Byrne

Bibliographic record

VenueCase Reports in Gastrointestinal Medicine · 2012
Typearticle
Languageen
FieldMedicine
TopicGallbladder and Bile Duct Disorders
Canadian institutionsVancouver General HospitalUniversity of British Columbia
Fundersnot available
KeywordsEndoscopic retrograde cholangiopancreatographyMedicineImpactionForcepsSurgeryBile ductCommon bile duct stoneCommon bile ductBalloon

Abstract

fetched live from OpenAlex

Biliary extraction baskets are a commonly used instrument for the removal of choledocholithiasis in endoscopic retrograde cholangiopancreatography (ERCP). Impaction of the extraction basket is a recognized complication of ERCP, and is usually the result of discrepancy between the size of bile duct stone and the diameter of the distal bile duct. Whilst mechanical lithotriptors can be used to crush the stone or break the wires of the basket to allow its release, failure of the lithotriptor device can occur. We describe the case of a 59-year-old gentleman who had an ERCP performed for choledocholithiasis. Basket impaction was encountered, and the mechanical lithotriptor failed to dislodge the stone/basket complex. A two-step technique involving balloon dilatation and forceps manipulation of the basket was applied to successfully dislodge the impacted basket. We believe this simple and safe technique should be adopted to rescue impacted biliary extraction baskets to avoid the need for potential surgical removal.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.003
Open science0.0030.003
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.003

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 head0.039
GPT teacher head0.335
Teacher spread0.296 · 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 designCase report
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

Citations11
Published2012
Admission routes1
Has abstractyes

Explore more

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