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Record W1996991606 · doi:10.1097/mog.0b013e3283025c57

The nonerosive reflux disease???gastroesophageal reflux disease controversy

2008· review· en· W1996991606 on OpenAlexaboutno aff
Jack Winter, R C Heading

Bibliographic record

VenueCurrent Opinion in Gastroenterology · 2008
Typereview
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsRefluxDiseaseMedicineGastroenterologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE OF REVIEW: To analyse the concept of nonerosive reflux disease (NERD), examining its evolving definition and its relationship to reflux disease and functional gastrointestinal disorders. RECENT FINDINGS: The advent of the Montreal definition of gastroesophageal reflux disease (GERD) and the Rome III definition of functional upper gastrointestinal disorders has refined the concept of NERD. The high prevalence of GERD symptoms and the strong overlap between GERD and irritable bowel syndrome is due to the influence of NERD. Subtle differences exist between patterns of acid exposure in NERD and erosive disease on pH testing. Symptom generation in NERD may be influenced by altered mucosal permeability. Improvements in endoscopic technology demonstrate esophageal mucosal changes in NERD which are not seen in controls. There is a general acknowledgement that the inferior symptomatic response to acid suppression reported in NERD is attributable, at least in part, to contamination of study populations by patients with functional heartburn. SUMMARY: NERD is common and its definition continues to evolve. For the present, however, this should be considered to be heartburn with and without regurgitation due to gastroesophageal reflux in the absence of esophageal mucosal erosions. Future studies examining treatment response of GERD subgroups must exclude functional heartburn if NERD is to be properly understood.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.885
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.076
GPT teacher head0.400
Teacher spread0.324 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
Domainnot available
GenreReview

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

Citations19
Published2008
Admission routes1
Has abstractyes

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