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Record W3015592303 · doi:10.14745/ccdr.v46i04a01

Overview of the respiratory syncytial virus vaccine candidate pipeline in Canada

2020· article· en· W3015592303 on OpenAlexafffundvenueabout
April Killikelly, Matthew Tunis, Althea House, Caroline Quach, Wendy Vaudry, Dorothy Moore

Bibliographic record

VenueCanada Communicable Disease Report · 2020
Typearticle
Languageen
FieldMedicine
TopicRespiratory viral infections research
Canadian institutionsMcGill UniversityStollery Children's HospitalUniversity of AlbertaUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustinePublic Health Agency of Canada
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsVirologyVirusRespiratory systemPipeline (software)MedicineComputer scienceInternal medicine

Abstract

fetched live from OpenAlex

A vaccine for respiratory syncytial virus (RSV) has been actively sought for over 60 years due to the health impacts of RSV disease in infants, but currently the only available preventive measure in Canada and elsewhere is limited to passive immunization for high-risk infants and children with a monoclonal antibody. RSV vaccine development has faced many challenges, including vaccine-induced enhancement of RSV disease in infants. Several key developments in the last decade in the fields of cellular immunology and protein structure have led to new products entering late-stage clinical development. As of July 2019, RSV vaccine development is being pursued by 16 organizations in 121 clinical trials. Five technologies dominate the field of RSV vaccine development, four active immunizing agents (live-attenuated, particle-based, subunit-based and vector-based vaccines) and one new passive immunizing agent (monoclonal antibody). Phase 3 clinical trials of vaccine candidates for pregnant women, infants, children and older adults are under way. The next decade will see a dramatic transformation of the RSV prevention landscape.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.355
Threshold uncertainty score0.953

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.071
GPT teacher head0.335
Teacher spread0.263 · 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 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

Citations20
Published2020
Admission routes4
Has abstractyes

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