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Record W1974700394 · doi:10.1136/sti.77.5.387

Trends of gonorrhoea and early syphilis in Belgrade, 1985-99

2001· article· en· W1974700394 on OpenAlexaff
Milan Bjekić

Bibliographic record

VenueSexually Transmitted Infections · 2001
Typearticle
Languageen
FieldMedicine
TopicSyphilis Diagnosis and Treatment
Canadian institutionsSKiN Health
Fundersnot available
KeywordsMedicineSyphilisGonorrheaVirologySyphilis SerodiagnosisGynecologyHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

Sexually transmitted diseases represent a major public health problem and the advent of HIV infection during the past decade has highlighted the importance of infections spread by the sexual route. The purpose of this study was to report trends of gonorrhoea and early syphilis in the Belgrade population (about two million inhabitants) during the period 1985–99, and to discuss the data in the light of changes in gonorrhoea and syphilis rates in other countries of eastern Europe. Primary, secondary, and early latent syphilis (referred to as early syphilis) were defined using generally accepted criteria. For diagnosis of early syphilis the Venereal Disease Research Laboratory (VDRL) and Treponema pallidum haemagglutination (TPHA) tests were used. For diagnosis of gonorrhoea standard laboratory examination was used—that is, microscopy and inoculation on culture media. Reporting on syphilis and gonorrhoea is compulsory in Yugoslavia. In Belgrade all reports are sent to the municipal department for skin and venereal diseases. These reports were used as the source of data for incidence cases. The incidence rates for syphilis and gonorrhoea were calculated using data from the 1991 Yugoslav census for the Belgrade population. Age adjustment of yearly incidence was carried out by a direct method using the “World population” as the standard. Data about possible source of infection, provided on the official form for notification of syphilis and gonorrhoea, were also analysed. The early syphilis incidence rates in men showed a decreasing trend during the first half of the period observed, followed by an …

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)0.000
metaresearch head score (Gemma)0.000
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 score0.060
Threshold uncertainty score0.669

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.017
GPT teacher head0.274
Teacher spread0.257 · 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

Citations8
Published2001
Admission routes1
Has abstractyes

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