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Record W2762530524 · doi:10.2217/fmb-2017-0078

Examining Sociodemographic Risk Factors for <i>Chlamydia Trachomatis</i> Infection: a Population-based Cohort Study

2017· article· en· W2762530524 on OpenAlexafffundabout
Ranjani Somayaji, Christopher Naugler, Maggie Guo, Deirdre L. Church

Bibliographic record

VenueFuture Microbiology · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
FundersCanadian Institutes of Health Research
KeywordsChlamydia trachomatisChlamydiaCohortMedicineCohort studyPopulationChlamydia trachomatis infectionChlamydial infectionRisk factorEnvironmental healthDemographyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

AIM: Chlamydia trachomatis is the most prevalent bacterial sexually transmitted infection in developed nations and is an important public health concern. We aimed to assess the factors associated with testing and positivity of C. trachomatis in a large population. METHODS: A retrospective study of a large Canadian health region was undertaken using 2011 census and laboratory data. Demographic and socioeconomic data from the national household survey were linked to microbiologic data for C. trachomatis. Multivariable generalized estimating equation models were constructed to examine relative risk for C. trachomatis testing and positivity. RESULTS: For testing and positivity, female sex and younger age groups were associated with increased risk. University education and South Asian ethnicity were associated with lower risk of positivity. CONCLUSION: Incorporating socio-demographic factors will be critical to the success of future sexually transmitted infection public health programs.

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 score0.304
Threshold uncertainty score0.605

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.298
Teacher spread0.273 · 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

Citations4
Published2017
Admission routes3
Has abstractyes

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