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Record W4410014285 · doi:10.1016/j.jpedcp.2025.200146

Brief Report: Trends of Congenital Syphilis among Neonates in Canada 2012-2023

2025· article· en· W4410014285 on OpenAlexaffabout
Chantal Nelson, Katarzyna Naczk, Ari Bitnun, Deborah Money, Geneviève Gravel, Joanna Merckx, Michiel Van den Hof, Heather Scott, Leah Thorp, Elisabeth McClymont, Prakesh S. Shah

Bibliographic record

VenueThe Journal of Pediatrics Clinical Practice · 2025
Typearticle
Languageen
FieldMedicine
TopicSyphilis Diagnosis and Treatment
Canadian institutionsMount Sinai HospitalMcGill UniversityIzaak Walton Killam Health CentreUniversity of ManitobaUniversity of British ColumbiaHospital for Sick ChildrenSaskatchewan HealthSickKids FoundationUniversity of TorontoUniversity of WaterlooPublic Health Agency of Canada
Fundersnot available
KeywordsCongenital syphilisSyphilisMedicinePediatricsEnvironmental healthFamily medicineHuman immunodeficiency virus (HIV)

Abstract

fetched live from OpenAlex

In Canada, incidence of congenital syphilis significantly increased from 2018 to 2023. Supporting enhanced public health preventive interventions such as early screening and treatment, particularly for younger women in lower socioeconomic strata and those with a history of addictive substance use, may reduce congenital syphilis.

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 score0.024
Threshold uncertainty score0.172

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.004
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.033
GPT teacher head0.375
Teacher spread0.342 · 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

Citations2
Published2025
Admission routes2
Has abstractyes

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