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Record W2103523936 · doi:10.1136/sextrans-2014-051732

Targeting core groups for gonorrhoea control: feasibility and impact

2015· review· en· W2103523936 on OpenAlexaff
Katia Giguère, Michel Alary

Bibliographic record

VenueSexually Transmitted Infections · 2015
Typereview
Languageen
FieldImmunology and Microbiology
TopicReproductive tract infections research
Canadian institutionsInstitut National de Santé Publique du QuébecUniversité LavalCentre hospitalier de l'Université LavalHôpital du Saint-SacrementCentre hospitalier universitaire de Québec
Fundersnot available
KeywordsMedicineGonorrheaCore (optical fiber)Neisseria gonorrhoeaeGonococcal infectionGynecologySexually transmitted diseaseSyphilisVirologyMicrobiologyHuman immunodeficiency virus (HIV)Telecommunications

Abstract

fetched live from OpenAlex

OBJECTIVE: We aimed to outline why core groups should be targeted in Neisseria gonorrhoeae control and suggest several important and timely interventions to target core groups while highly resistant strains are spreading. METHODS: Core group definition, feasibility and impact of gonorrhoea core group interventions as well as gonorrhoea resistance development have been reviewed in the paper. RESULTS: Core group interventions have proven effective in gonorrhoea control in the past but are compromised by the spread of highly resistant strains. CONCLUSIONS: Worldwide functional Gonorrhoea Antimicrobial Surveillance Program, better screening and better treatment programmes are needed. Prevention through condom promotion aimed at core groups remains essential. More specific treatment guidance for low-income and middle-income countries without resistance data is required in the meantime to achieve a better use of antibiotics.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.087
GPT teacher head0.395
Teacher spread0.308 · 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 designSystematic review
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

Citations6
Published2015
Admission routes1
Has abstractyes

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