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Record W2107423446 · doi:10.1017/s0950268810001160

Burden of acute gastrointestinal illness in the Metropolitan region, Chile, 2008

2010· article· en· W2107423446 on OpenAlexafffund
M. Kate Thomas, Enrique Chinarro Pérez, Shannon E. Majowicz, Richard J. Reid‐Smith, Andrea Olea, José A. Díaz, Vicky Solari, Scott A. McEwen

Bibliographic record

VenueEpidemiology and Infection · 2010
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of GuelphPublic Health Agency of Canada
FundersPan American Health OrganizationInternational Development Research CentrePublic Health AgencyPublic Health Agency of CanadaUniversidad Iberoamericana Ciudad de MéxicoUniversity of Guelph
KeywordsMedicineMetropolitan areaDemographyPopulationIncidence (geometry)Environmental health

Abstract

fetched live from OpenAlex

The purpose of this study was to determine the magnitude and distribution of acute gastrointestinal illness (GI) in the Chilean population, describe its burden and presentation, identify risk factors associated with GI and assess the differences between a 7-day, 15-day and a 30-day recall period in the population-based burden of illness study design. Face-to-face surveys were conducted on 6047 randomly selected residents in the Metropolitan region, Chile (average response rate 75·8%) in 2008. The age-adjusted monthly prevalence of GI was 9·2%. The 7-day recall period provided annual incidence rate estimates about 2·2 times those of the 30-day recall period. Age, occupation, healthcare system, sewer system, antibiotic use and cat ownership were all found to be significant predictors for being a case. This study expands on the discussion of recall bias in retrospective population studies and reports the first population-based burden and distribution of GI estimates in Chile.

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)0.002
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation 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 score0.012
Threshold uncertainty score0.560

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.030
GPT teacher head0.343
Teacher spread0.312 · 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 teacher head, 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

Citations23
Published2010
Admission routes2
Has abstractyes

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