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Record W4389833960 · doi:10.1002/9781119525127.ch9

Advanced Endoscopic Procedures

2023· other· en· W4389833960 on OpenAlexaff
Catharine M. Walsh MD MEd PhD FRCPC, Ahmir Ahmad MBBS BSc MRCP, Brian P. Saunders MD FRCP FRCS, Jonathan Cohen MD FASGE FACG, Peter B. Cotton MD FRCP FRCS, Christopher B. Williams BM FRCP FRCS, Stephen Preston

Bibliographic record

Venuenot available
Typeother
Languageen
FieldMedicine
TopicPancreatic and Hepatic Oncology Research
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsEndoscopic retrograde cholangiopancreatographyMedicineEndoscopic ultrasoundMajor duodenal papillaEndoscopic submucosal dissectionRadiologyEndoscopySurgeryPancreatitis

Abstract

fetched live from OpenAlex

This chapter provides a brief introduction to some of the advanced endoscopic procedures. First attempted just over 50 years ago, endoscopic cannulation of the papilla of Vater was a true revolution, allowing injection of contrast to the pancreatic and biliary ductal systems to produce diagnostic radiographs before there were any abdominal scans. The dramatic imaging developments in recent decades (ultrasound, CT and MR scanning, and endoscopic ultrasound) have almost eliminated the need for endoscopic retrograde cholangiopancreatography (ERCP) as a diagnostic procedure. ERCP differs in several ways from most commonly performed endoscopic procedures. Endoscopic ultrasound is widely used to examine mucosal and submucosal lesions and for suspected biliary and pancreatic diseases. Having largely conquered the mucosa, brave endoscopists have been probing deeper, opening up the “third space” below the mucosa. Endoscopic submucosal dissection allows removal of mucosal tumors in one piece, from below.

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)0.001
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: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.076
Threshold uncertainty score0.255

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0760.053

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 head0.030
GPT teacher head0.379
Teacher spread0.349 · 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
GenreOther

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
Published2023
Admission routes1
Has abstractyes

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