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Record W2989660952 · doi:10.1542/peds.2019-2541

Protecting Young Infants From Measles

2019· letter· en· W2989660952 on OpenAlexaboutno aff
Huong Q. McLean, Walter A. Orenstein

Bibliographic record

VenuePEDIATRICS · 2019
Typeletter
Languageen
FieldMedicine
TopicVirology and Viral Diseases
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineMeaslesPediatricsVirologyVaccination

Abstract

fetched live from OpenAlex

* Abbreviation: MMR — : measles-mumps-rubella vaccine In this issue of Pediatrics by Science et al,1 measles antibody levels were assessed in a cross-sectional sample of infants in Ontario, Canada, where endemic measles transmission has been eliminated since 1998. Antibody levels waned quickly, and all infants were considered susceptible to measles by age 6 months. The increased susceptibility to measles among younger infants in an elimination setting is not surprising and has been noted previously. Measles vaccine–induced maternal antibodies result in lower levels of passively acquired antibodies in infants.2,3 However, as the authors state, this leaves infants potentially susceptible to measles until they are old enough to receive the vaccine. In light of increasing measles outbreaks during the past year reaching levels not recorded in the United States since 1992 and increased measles elsewhere,4,5 coupled with the risk of severe illness in infants, there is increased concern regarding the protection of infants against measles. Current recommendations from the Advisory Committee on Immunization Practices allow measles vaccination as early as 6 months for infants who plan to travel internationally, infants with ongoing risk for exposure during measles outbreaks, and as postexposure prophylaxis.6 For routine vaccination, … Address correspondence to Walter A. Orenstein, MD, Emory Vaccine Center, Emory University School of Medicine, 1462 Clifton Rd NE, Suite 446, Atlanta, GA 30322. E-mail: worenst{at}emory.edu

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)0.005
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: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0080.005
Insufficient payload (model declined to judge)0.0040.003

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 head0.021
GPT teacher head0.264
Teacher spread0.242 · 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
GenreEditorial

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

Citations0
Published2019
Admission routes1
Has abstractyes

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