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Record W2289368494 · doi:10.1155/2014/501043

Small Bowel Obstruction Following Computed Tomography and Magnetic Resonance Enterography Using Psyllium Seed Husk As an Oral Contrast Agent

2014· article· en· W2289368494 on OpenAlexaff
Yingming Amy Chen, Patrick Cervini, Anish Kirpalani, Paraskevi A. Vlachou, Samir C. Grover, Errol Colak

Bibliographic record

VenueCanadian Journal of Gastroenterology and Hepatology · 2014
Typearticle
Languageen
FieldMedicine
TopicEsophageal and GI Pathology
Canadian institutionsWindsor Regional HospitalSt. Michael's Hospital
Fundersnot available
KeywordsMedicineMagnetic resonance imagingComputed tomographyPsylliumRadiologyContrast mediumComplicationHuskContrast (vision)SurgeryDietary fiber

Abstract

fetched live from OpenAlex

The authors report a case series describing four patients who developed small bowel obstruction following the use of psyllium seed husk as an oral contrast agent for computed tomography or magnetic resonance enterography. Radiologists who oversee computed tomography and magnetic resonance enterography should be aware of this potential complication when using psyllium seed husk and other bulking agents, particularly when imaging patients with known or suspected small bowel strictures or active inflammation.

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)0.006
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: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.002
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.002
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 head0.015
GPT teacher head0.232
Teacher spread0.217 · 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

Citations10
Published2014
Admission routes1
Has abstractyes

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