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Record W3016179483 · doi:10.1159/000504477

Vaccination against Respiratory Syncytial Virus

2020· review· en· W3016179483 on OpenAlexaff
Christopher Green, Simon B. Drysdale, Andrew J. Pollard, Charles Sande

Bibliographic record

VenueInterdisciplinary topics in gerontology and geriatrics · 2020
Typereview
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsVaccinationImmunityImmunologyMedicineDiseasePopulationVirologyImmune systemHerd immunityIntensive care medicineEnvironmental healthInternal medicine

Abstract

fetched live from OpenAlex

Respiratory syncytial virus (RSV) causes infection throughout life, with infants, adults who are severely immunocompromised, and the elderly at special risk of developing lower respiratory tract disease, hospitalisation, and death. The burden of severe disease in the elderly is comparable to seasonal influenza, and there remains no effective anti-viral drugs or vaccine for any target population. The development of a vaccine to confer immunity against severe disease is a major global health priority. A multitude of safe and immunogenic vaccine candidates have failed to induce the protective immunity needed for licensure, and in recent years this has included the largest clinical trials of RSV vaccines in history. The obstacles to vaccine development in elderly populations include an incomplete understanding of the immune responses needed for protection, the effect of aging on induction and maintenance of immunity (natural and vaccine induced immunity), and the high rate of co-morbid disease in older adults. Recent advances in structural biology, new biological platforms for antigen delivery, and insights from experimental challenge models mark the latest developments in over 50 years of research. This continues to be an active and evolving field of scientific discovery with renewed hope for a vaccine in the future.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0010.002
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 head0.105
GPT teacher head0.448
Teacher spread0.342 · 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.

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

Citations8
Published2020
Admission routes1
Has abstractyes

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