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Record W4377116058 · doi:10.1186/s12905-023-02433-w

Correction to: Prevalence of depression, syndemic factors and their impact on viral suppression among female sex workers living with HIV in eThekwini, South Africa

2023· erratum· en· W4377116058 on OpenAlexaff
Anvita Bhardwaj, Carly A. Comins, Vijay Guddera, Mfezi Mcingana, Katherine Young, René Phetlhu, Ntambue Mulumba, Sharmistha Mishra, Harry Hausler, Stefan Baral, Sheree Schwartz

Bibliographic record

VenueBMC Women s Health · 2023
Typeerratum
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSyndemicHuman immunodeficiency virus (HIV)Depression (economics)MedicineEnvironmental healthDemographyVirologySociology

Abstract

fetched live from OpenAlex

Introduction Over half of female sex workers (FSW) in South Africa are living with HIV and clinical depression has been frequently documented among FSW. Data characterizing structural determinants of depression and the role of syndemic theory, synergistically interacting disease states, on viral suppression among FSW in South Africa are limited. Methods: Between July 2018-March 2020, non-pregnant, cisgender women (≥ 18 years), reporting sex work as their primary income source, and diagnosed with HIV for ≥ 6 months were enrolled into the Siyaphambili trial in eThekwini, South Africa. Using baseline data, robust Poisson regression models were used to assess correlates of depression and associations between depression and syndemic factors on viral suppression.

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)0.006
metaresearch head score (Gemma)0.103
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: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.161
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.103
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0040.005
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0040.002
Research integrity0.0030.006
Insufficient payload (model declined to judge)0.1610.039

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 head0.023
GPT teacher head0.312
Teacher spread0.289 · 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
GenreOther

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

Citations3
Published2023
Admission routes1
Has abstractyes

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