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Record W3025246827 · doi:10.1503/cjs.003019

Interventional radiology-assisted transgastric endoscopic drainage of peripancreatic fluid collections

2020· article· en· W3025246827 on OpenAlexaffvenue
Jeffrey Hawel, Heather McFadgen, R. D. Stewart, Tarek H. El-Ghazaly, Abdulrahim Alawashez, James Ellsmere

Bibliographic record

VenueCanadian Journal of Surgery · 2020
Typearticle
Languageen
FieldMedicine
TopicPancreatitis Pathology and Treatment
Canadian institutionsDalhousie University
Fundersnot available
KeywordsMedicineEndoscopic ultrasoundRadiologyEndoscopyEndoscopic ultrasonographyPancreatitisDrainagePancreatic pseudocystLumen (anatomy)Computed tomographyInterventional radiologyCystSurgery

Abstract

fetched live from OpenAlex

Summary: Peripancreatic fluid collections (PFCs) occur as a consequence of pancreatitis. Most PFCs resolve spontaneously, although 1%-2% persist and may require intervention. Conventional transluminal endoscopic drainage methods require the PFC to be bulging into the gastric wall; however, it is not uncommon for this to be absent. Imaging guidance for transluminal endoscopic PFC drainage allows the endoscopist to localize nonbulging pseudocysts that cannot be localized using endoscopy alone, to identify and avoid vascular structures between the cyst and the gastric lumen, and to reveal solid or necrotic components within the pseudocyst cavity. Although endoscopic ultrasound (EUS) has been used to meet this need, timely access to therapeutic EUS remains a limiting factor at many centres. We report our technique and experience performing transgastric endoscopic drainage of PFCs under computed tomography (CT) interventional radiology guidance.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.052
GPT teacher head0.256
Teacher spread0.204 · 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 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

Citations3
Published2020
Admission routes2
Has abstractyes

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Same venueCanadian Journal of SurgerySame topicPancreatitis Pathology and TreatmentFrench-language works237,207