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Record W4293000380 · doi:10.54097/hset.v8i.1206

A Review on the Diagnosis and Treatment of Syphilis

2022· review· en· W4293000380 on OpenAlexaff
Qianqi Chen, Yiyao Yang

Bibliographic record

VenueHighlights in Science Engineering and Technology · 2022
Typereview
Languageen
FieldMedicine
TopicSyphilis Diagnosis and Treatment
Canadian institutionsQueen's University
Fundersnot available
KeywordsSyphilisMedicineAzithromycinSexually transmitted diseaseDoxycyclinePrimary SyphilisLatent SyphilisPenicillinAntibioticsCeftriaxoneCongenital syphilisImmunologyVirologyHuman immunodeficiency virus (HIV)TreponemaMicrobiologyBiology

Abstract

fetched live from OpenAlex

Syphilis is a multi-phase sexually transmitted disease through contacting with a partner infected by syphilis or from a gravida to her newborn congenitally. The reappearance of syphilis is a severe public health concern, particularly because syphilis lesions would boost the chance of acquiring and spreading human immunodeficiency virus (HIV) infection. A dose of benzathine penicillin G (BPG) through intramuscular injection is the current treatment for syphilis, which is the optimal treatment for all stages of syphilis. Although some alternatives such as doxycycline and ceftriaxone are also evidently effective, the optimal therapy is still BPG, especially in latent syphilis and pregnancy. Because of the clinically significant azithromycin resistance, this second-line medication is no longer used routinely. Currently, macrolide resistance is the only antibiotic resistance with clinical evidence. Even though still no vaccine is published for syphilis, syphilis is a promising disease for vaccine development. The vaccine for syphilis is currently under research. This paper contained information about the pathological process, symptoms, diagnosis of syphilis, and effective treatment using antibiotics. The review also discussed future vaccine directions.

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)0.001
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 score0.007
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.003

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 head0.060
GPT teacher head0.321
Teacher spread0.261 · 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

Citations1
Published2022
Admission routes1
Has abstractyes

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