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Record W2308163573 · doi:10.1080/21645515.2015.1120393

Current status of new tuberculosis vaccine in children

2016· review· en· W2308163573 on OpenAlexaff
Yu Pang, Aihua Zhao, Chad Cohen, Wanli Kang, Jie Lu, Guozhi Wang, Yanlin Zhao, Suhua Zheng

Bibliographic record

VenueHuman Vaccines & Immunotherapeutics · 2016
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcGill UniversityMcGill University Health Centre
FundersAmerican Educational Research Association
KeywordsMedicineImmunogenicityVaccinationTuberculosisBCG vaccineTuberculosis vaccinesIntensive care medicineClinical trialDiseaseTransmission (telecommunications)ImmunologyVaccine efficacyMeningitisPediatricsMycobacterium tuberculosisImmune systemInternal medicine

Abstract

fetched live from OpenAlex

Pediatric tuberculosis contributes significantly to the burden of TB disease worldwide. In order to achieve the goal of eliminating TB by 2050, an effective TB vaccine is urgently needed to prevent TB transmission in children. BCG vaccination can protect children from the severe types of TB such as TB meningitis and miliary TB, while its efficacy against pediatric pulmonary TB ranged from no protection to very high protection. In recent decades, multiple new vaccine candidates have been developed, and shown encouraging safety and immunogenicity in the preclinical experiments. However, the limited data on protective efficacy in infants evaluated by clinical trials has been disappointing, an example being MVA85A. To date, no vaccine has been shown to be clinically safer and more effective than the presently licensed BCG vaccine. Hence, before a new vaccine is developed with more promising efficacy, we must reconsider how to better use the current BCG vaccine to maximize its effectiveness in children.

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)0.001
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: Review · Consensus signal: Review
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.002

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 head0.079
GPT teacher head0.420
Teacher spread0.341 · 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
GenreReview

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

Citations36
Published2016
Admission routes1
Has abstractyes

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