MétaCan
Menu
Back to cohort
Record W2234552080 · doi:10.1093/pch/19.2.91

Immunization for meningococcal serogroup B: What does the practitioner need to know?

2014· article· en· W2234552080 on OpenAlexaboutno aff
Joan Robinson

Bibliographic record

VenuePaediatrics & Child Health · 2014
Typearticle
Languageen
FieldImmunology and Microbiology
TopicBacterial Infections and Vaccines
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeningococcal diseaseImmunizationMeningococcal vaccineRoutine immunizationIncidence (geometry)Intensive care medicinePediatricsScheduleNeisseria meningitidisVaccinationImmunologyBiology

Abstract

fetched live from OpenAlex

Most invasive meningococcal disease in Canada is now caused by serogroup B organisms. A vaccine directed against this serogroup (4CMenB) is newly licensed in Canada. A decision will need to be made by all provinces and territories regarding whether a routine infant immunization program is warranted. This decision will need to take into account factors such as uncertain estimates for the effectiveness of the vaccine, the high incidence of fever from the vaccine and the burden of introducing more injections into the current immunization schedule, and consider them against the potentially preventable mortality and morbidity that result from a rare but very serious disease.

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)0.008
metaresearch head score (Gemma)0.032
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: Empirical · Consensus signal: none
Teacher disagreement score0.015
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0020.001
Science and technology studies0.0020.004
Scholarly communication0.0040.013
Open science0.0020.002
Research integrity0.0150.016
Insufficient payload (model declined to judge)0.0080.006

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 head0.009
GPT teacher head0.264
Teacher spread0.255 · 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
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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venuePaediatrics & Child HealthSame topicBacterial Infections and VaccinesFrench-language works237,207