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Record W2768057291 · doi:10.1071/ma17064

Changing epidemiology of invasive meningococcal disease in Australia 1994–2016

2017· article· en· W2768057291 on OpenAlexaff
Helen Smith, Amy V. Jennison

Bibliographic record

VenueMicrobiology Australia · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsEpidemiologyMedicineCase fatality rateOutbreakIncidence (geometry)DiseaseMeningitisMeningococcal diseaseVaccinationPublic healthPediatricsNeisseria meningitidisIntensive care medicineImmunologyInternal medicineVirologyPathologyBiology

Abstract

fetched live from OpenAlex

Invasive meningococcal disease (IMD) has a relatively low incidence in Australia, however remains a serious public health issue, with a case fatality rate of approximately 10% despite antimicrobial treatment. IMD is particularly seen in young children, but can affect all age groups. The disease has non-specific early symptoms, rapid clinical progression mainly manifesting as septicaemia and/or meningitis, and has the potential for long term sequelae in the survivors, including skin scarring, amputation, deafness and seizures. There are 13 serogroups, although most invasive infections worldwide are caused by serogroups A, B, C, W, and Y, with some recent outbreaks in Africa caused by serogroup X. The prevalent circulating serogroups can undergo dynamic shifts, generating dramatic changes in IMD epidemiology. Such serogroup shifts have important ramifications for vaccination programs and constant surveillance is crucial.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.239
Threshold uncertainty score0.475

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.074
GPT teacher head0.340
Teacher spread0.265 · 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

Citations1
Published2017
Admission routes1
Has abstractyes

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