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Record W1925068812 · doi:10.1155/2002/459638

Motion – All Patients with GERD Should Be Offered Once in a Lifetime Endoscopy: Arguments against the Motion

2002· article· en· W1925068812 on OpenAlexvenueno aff
James W. Freston

Bibliographic record

VenueCanadian Journal of Gastroenterology · 2002
Typearticle
Languageen
FieldMedicine
TopicEsophageal Cancer Research and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsGERDMedicineEndoscopyDysplasiaDiseaseEsophagusEsophageal adenocarcinomaRefluxGeneral surgeryInternal medicineGastroenterologyAdenocarcinomaCancer

Abstract

fetched live from OpenAlex

The evidence for the recommendation that patients with gastroesophageal reflux disease (GERD) be offered once in a lifetime endoscopy is weak and is not supported by any clinical trials. GERD is a very prevalent condition, yet only 10% of patients with GERD have Barrett's esophagus (BE). Esophageal adenocarcinoma (EAC) is a rare condition and is uncommon even among patients with BE. A decision analysis found that surveillance of BE patients is performed because of inflated estimates of the rate of progression from BE to EAC. Dysplasia more often regresses to more benign histological findings than to cancer, and transient dysplasia can also lead to a high rate of unnecessary endoscopy. Even though practice guidelines about endoscopic surveillance have been published, there is no consensus among gastroenterologists about appropriate protocols, and many physicians are more aggressive than the guidelines. It has not been proved that surveillance saves lives, in part because BE rarely leads to death from EAC. The favourable results from some specialized centres may not be widely applicable. The recommendation for 'once in a lifetime' endoscopy for GERD patients is premature.

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)0.031
metaresearch head score (Gemma)0.124
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.039
Threshold uncertainty score0.163

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0310.124
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0010.001
Science and technology studies0.0030.010
Scholarly communication0.0030.006
Open science0.0040.003
Research integrity0.0390.028
Insufficient payload (model declined to judge)0.0110.006

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 head0.264
Teacher spread0.234 · 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
GenreCommentary

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

Citations2
Published2002
Admission routes1
Has abstractyes

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Same venueCanadian Journal of GastroenterologySame topicEsophageal Cancer Research and TreatmentFrench-language works237,207