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Record W2773600626 · doi:10.1097/inf.0000000000001850

Invasive Haemophilus Influenzae Type B Infections in Children with Cancer in the Era of Infant HIB Immunization Programs (1991–2014)

2017· article· en· W2773600626 on OpenAlexaffabout
Joanne McNair, Alyssa E. Smith, Julie A. Bettinger, Wendy Vaudry, Ben Tan, Shalini Desai, Scott A. Halperin, Karina A. Top

Bibliographic record

VenueThe Pediatric Infectious Disease Journal · 2017
Typearticle
Languageen
FieldMedicine
TopicPneumonia and Respiratory Infections
Canadian institutionsIzaak Walton Killam Health CentrePublic Health Agency of CanadaRoyal University HospitalUniversity of SaskatchewanUniversity of AlbertaDalhousie UniversityBC Children's HospitalUniversity of British ColumbiaStollery Children's Hospital
Fundersnot available
KeywordsMedicineImmunizationHib vaccinePediatricsEpidemiologyHaemophilus influenzaePediatric cancerVaccinationBooster (rocketry)Active immunizationBooster doseCancerImmunologyConjugate vaccineInternal medicineAntibodyAntibioticsMicrobiology

Abstract

fetched live from OpenAlex

We studied the epidemiology of Haemophilus influenzae type b infections among children with cancer admitted to Canadian pediatric hospitals. From 1991 to 2014, 13 cases among children with cancer were identified through active surveillance. Average age was 6.7 years. Six of 7 cases eligible for infant immunization were age-appropriately immunized (vaccine failures). Children with cancer may benefit from booster Hib immunization.

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)0.002
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 score0.829
Threshold uncertainty score0.345

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.279
Teacher spread0.267 · 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

Citations4
Published2017
Admission routes2
Has abstractyes

Explore more

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