MétaCan
Menu
Back to cohort
Record W1988795130 · doi:10.1586/14760584.6.4.539

Heterologous boost vaccines for bacillus Calmette–Guérin prime immunization against tuberculosis

2007· review· en· W1988795130 on OpenAlexaff
Zhou Xing, Thomas James Charters

Bibliographic record

VenueExpert Review of Vaccines · 2007
Typereview
Languageen
FieldMedicine
TopicTuberculosis Research and Epidemiology
Canadian institutionsMcMaster UniversityMcMaster University Medical Centre
Fundersnot available
KeywordsHeterologousImmunizationVirologyBacillus (shape)TuberculosisVaccinationBCG vaccineMedicineMicrobiologyImmunologyBiologyAntigenGeneticsPathology

Abstract

fetched live from OpenAlex

The current tuberculosis (TB) epidemic continues to call for the development of effective vaccination strategies. The initial TB vaccine research effort mostly focused on the search for a vaccine that might be better than, and thus could replace, the current bacillus Calmette-Guérin (BCG) vaccine. It has increasingly been realized that BCG or an improved BCG will continue to be used as a prime TB vaccine and there is a need to develop effective boost vaccines that could enhance and prolong the protective immunity of BCG prime immunization. Mounting experimental evidence suggests that recombinant vaccines, including both recombinant protein and genetic vector vaccines, are effective in boosting immune activation and protection by BCG vaccination. This review will discuss recent advances and the authors' views in the development of there boost vaccines.

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 score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.004

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 head0.071
GPT teacher head0.434
Teacher spread0.363 · 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

Citations37
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueExpert Review of VaccinesSame topicTuberculosis Research and EpidemiologyFrench-language works237,207