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Record W7047777808

Health Services Use and HIV Prevalence Among Migrant and National Female Sex Workers in Portugal: Are We Providing the Services Needed?

2016· article· en· W7047777808 on OpenAlexaboutno aff

Bibliographic record

VenueRepositório Comum (Repositório Científico de Acesso Aberto de Portugal) · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
Fundersnot available
KeywordsSerostatusQuarter (Canadian coin)Human immunodeficiency virus (HIV)Health servicesMigrant workersSex workersHealth careFemale sexSex work
DOInot available

Abstract

fetched live from OpenAlex

This cross-sectional bio-behavioral survey conducted with 853 female sex workers (FSW) aimed to examine differences in use of HIV health services, testing and prevalence among migrant and national FSW. A quarter of undocumented FSW had never used National Health Service (NHS) and 15 % never tested for HIV, significantly more than nationals (p < 0.001 and p = 0.024, respectively). HIV infection was self-reported by 11.9 % of nationals, 1.8 % of documented and 0.8 % of undocumented migrants (p < 0.001). The HIV rapid test was reactive in 13.6 % of undocumented, 8.0 % of nationals and 2.3 % of documented. A higher proportion of migrants were unaware of their positive serostatus compared to nationals. Ever had HIV testing was less likely among undocumented, who never used the NHS and who didn't know where to go if suspected being HIV-infected. Promoting early diagnosis with linkage to care among migrant FSW should be supported, while developing health services better tailored to their needs.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.257
Teacher spread0.242 · 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
Published2016
Admission routes1
Has abstractyes

Explore more

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