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Record W2018145967 · doi:10.1177/1757913912445688

STI epidemiology in the global older population: emerging challenges

2012· review· en· W2018145967 on OpenAlexfundno aff
Victor Minichiello, Saifur Rahman, Gail Hawkes, Marian Pitts

Bibliographic record

VenuePerspectives in Public Health · 2012
Typereview
Languageen
FieldMedicine
TopicSexual function and dysfunction studies
Canadian institutionsnot available
FundersCenters for Disease Control and PreventionPublic Health Agency of Canada
KeywordsEpidemiologyChinaMedicineReproductive healthGlobal healthPopulationEnvironmental healthPublic healthGerontologyGeography

Abstract

fetched live from OpenAlex

This paper reviews the evidence concerning the epidemiology of sexually transmitted infections (STIs) with a particular focus on older people. Evidence from North America, Australia, China and Korea clearly shows increasing rates of many STIs in the population group aged 50 years and older. Similar changes are identified in three studies conducted in sub-Saharan Africa. There is a significant lack of detailed epidemiological data from Asia-Pacific and many African countries. There is also a lack of health education and health programmes directed towards older people. It is likely that sexual ageism is the dynamic that underpins this lack of focus and resources for older people.

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)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.004
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0020.002
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 head0.560
GPT teacher head0.530
Teacher spread0.030 · 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 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

Citations96
Published2012
Admission routes1
Has abstractyes

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