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Record W1577673418 · doi:10.1155/2009/374138

Argon Photocoagulation in the Treatment of Gastric Antral Vascular Ectasia and Radiation Proctitis

2009· article· en· W1577673418 on OpenAlexaffvenue
Greg Rosenfeld, Robert Enns

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2009
Typearticle
Languageen
FieldMedicine
TopicGastrointestinal Bleeding Diagnosis and Treatment
Canadian institutionsSt. Paul's HospitalUniversity of British Columbia
Fundersnot available
KeywordsMedicineArgon plasma coagulationRadiation proctitisGastric antral vascular ectasiaEctasiaProctitisRadiation therapyRectumGastrointestinal tractSurgeryGastroenterologyRadiologyInternal medicineEndoscopy

Abstract

fetched live from OpenAlex

Gastric antral vascular ectasia (GAVE) and radiation proctitis are two vascular disorders of the gastrointestinal tract that typically present with recurrent gastrointestinal bleeding. Although the pathogenesis of either condition is not known, they are unlikely to be similar. GAVE appears to be related to autoimmune disorders or cirrhosis, while radiation proctitis is the result of pelvic irradiation, most commonly used for the treatment of pelvic malignancies. Medical therapies for both conditions are not typically effective, and surgical therapies are usually not required because endoscopic treatment, aimed at coagulation of the underlying vascular lesions, has evolved as the most effective therapy. There is limited evidence in the literature for the use of medical and surgical therapies, with most of the evidence coming from case reports involving small numbers of patients. In the present article, we review the evidence for the use of argon plasma photocoagulation (APC, the most commonly used endoscopic modality) in the treatment of GAVE and radiation proctitis.

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: none
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.244
Teacher spread0.231 · 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

Citations29
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of GastroenterologySame topicGastrointestinal Bleeding Diagnosis and TreatmentFrench-language works237,207