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Record W2465170492 · doi:10.1385/1-59259-399-2:211

Microencapsulation of Vaccine Antigens

2003· article· en· W2465170492 on OpenAlexaff
David H. Jones

Bibliographic record

VenueHumana Press eBooks · 2003
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTransgenic Plants and Applications
Canadian institutionsGDI Integrated Facility Services (Canada)
Fundersnot available
KeywordsVaccinationMedicineSAFERPsychological interventionBooster (rocketry)Cold chainHealth careImmunizationIntensive care medicineImmunologyAntigenComputer scienceNursingEngineeringComputer securityPolitical science

Abstract

fetched live from OpenAlex

Despite obvious successes in controlling most serious childhood infections, there is a need to develop cheaper and more effective programs in infant vaccination. However, with the knowledge that adults are susceptible to diseases once believed to be only relevant to children, these criteria are equally applicable to adult vaccination programs. Furthermore, with the emphasis on safety, the vaccine industry is slowly replacing existing vaccines with recombinant alternatives that are safer and less reactogenic than their nonrecombinant counterparts, yet also less immunogenic. Thus, any improvements to vaccines in the foreseeable future are likely to arise through the introduction of better adjuvants and delivery systems. For example, a single injection comprising primary and booster doses of vaccine would improve compliance in a cost-effective manner by reducing the number of visits to clinics or medical centers. Equally, administering existing vaccines orally would remove the trauma of injection and the reliance on medical staff to perform the injections. Many vaccines are dependent on a cold chain; improving the stability of vaccines would thus help to reduce the cost of vaccination. To tackle such issues, researchers have borrowed ideas from other areas of the pharmaceutical industry in an attempt to improve the performance of vaccines and reduce the cost of these important health-care interventions.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.227

Codex and Gemma teacher scores by category

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

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 head0.027
GPT teacher head0.258
Teacher spread0.231 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations10
Published2003
Admission routes1
Has abstractyes

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