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Record W1996438666 · doi:10.4021/gr2009.06.1296

Heartburn in Staff of Golestan Medical University, Northeast of Iran

2009· article· en· W1996438666 on OpenAlexvenueno aff
Sima Besharat

Bibliographic record

VenueGastroenterology Research · 2009
Typearticle
Languageen
FieldMedicine
TopicGastroesophageal reflux and treatments
Canadian institutionsnot available
Fundersnot available
KeywordsHeartburnMedicineGERDRegurgitation (circulation)RefluxEtiologyIncidence (geometry)Internal medicineDiseaseGastroenterology

Abstract

fetched live from OpenAlex

BACKGROUND: Gastro-esophageal reflux disease (GERD) is the most common gastrointestinal disease in the west that has shown increasing incidence in Iran and Asian countries. The main presentations, described for GERD, are heartburn and acid regurgitation. METHODS: In this cross-sectional study in 2006, all personnel of Golestan Medical University (Northeast of Iran) were enrolled. A questionnaire consisting of demographic data, symptoms and risk factors was completed for all volunteers. Height and weight were measured. Chi-square and Non-parametric tests were used for analysis. RESULTS: Symptoms of heartburn were seen in 60% of all 155 studied subjects. No significant relationship was seen between symptoms and variables like age, gender, BMI and tribes. Symptoms were more common in married ones (P < 0.05). CONCLUSIONS: Heartburn prevalence was high in this study. Heartburn was seen more in women and in married. The probable underlying etiology and explanation for these results should be studied more.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.052
GPT teacher head0.373
Teacher spread0.321 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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