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Record W2995132257 · doi:10.1097/mpg.0000000000002584

Effect of Definitions of Acute Gastroenteritis Episodes Using Symptom Diaries in Paediatric Cohorts

2019· review· en· W2995132257 on OpenAlexfundno aff
Gabor Mihala, Keith Grimwood, Stephen B. Lambert, Robert S. Ware

Bibliographic record

VenueJournal of Pediatric Gastroenterology and Nutrition · 2019
Typereview
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsnot available
FundersMedical Research CouncilChildren's Health FoundationAustralian GovernmentNational Health and Medical Research CouncilGlaxoSmithKline
KeywordsMedicineObservational studyPediatricsIncidence (geometry)Cohort studyCohortAcute gastroenteritisVomitingProspective cohort studyEpidemiologyInternal medicine

Abstract

fetched live from OpenAlex

Estimates of acute gastroenteritis (AGE) burden are difficult to compare between studies because of inconsistent definitions describing this illness. AGE definitions used in prospective, community-based childhood cohort studies were identified by searching databases for studies that collected daily observations of AGE symptoms. Disease definitions and refractory periods were extracted. Data from the Australian community-based Observational Research in Childhood Infectious Diseases birth cohort were used to calculate AGE incidence and duration using identified AGE definitions, and the World Health Organization definition for diarrhoea. Eight distinct AGE definitions were identified. All included loose stools and 7 included vomiting as symptoms. The refractory period separating episodes ranged from 1 to 21 days. When applied to the Observational Research in Childhood Infectious Diseases dataset, AGE incidence ranged from 0.8 to 2.6 episodes per child-year-at-risk, a 3-fold relative difference. Direct comparisons of rates from different cohorts can only be undertaken if a standard definition for AGE is adopted.

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)0.018
metaresearch head score (Gemma)0.039
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.018
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0180.039
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0060.009
Bibliometrics0.0060.005
Science and technology studies0.0000.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.359
Teacher spread0.311 · 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 designSystematic review
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

Citations5
Published2019
Admission routes1
Has abstractyes

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