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Record W3096087928 · doi:10.1139/cjm-2020-0421

COVID-19 basics and vaccine development with a Canadian perspective

2020· review· en· W3096087928 on OpenAlexafffundvenueabout
Marina Liu, Daniel Chen

Bibliographic record

VenueCanadian Journal of Microbiology · 2020
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsUniversity of SaskatchewanUniversity of Calgary
FundersSaskatchewan Health Research Foundation
KeywordsCoronavirus disease 2019 (COVID-19)PandemicSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)CoronavirusTransmission (telecommunications)2019-20 coronavirus outbreakVirologyIsolation (microbiology)MedicineDiseaseIntensive care medicineImmunologyBiologyInfectious disease (medical specialty)OutbreakBioinformaticsComputer sciencePathology

Abstract

fetched live from OpenAlex

The ongoing coronavirus disease 2019 (COVID-19) pandemic is a rapidly evolving situation. New discoveries about COVID-19 and its causative virus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), continue to deepen the understanding of this novel disease. As there is currently no COVID-19 specific treatment, isolation is the most effective method to prevent transmission. Moreover, development of a safe and effective COVID-19 vaccine will be instrumental in reinstating pre-COVID-19 conditions. As of 31 July 2020, there are at least 139 vaccine candidates from around the globe in preclinical evaluation, with another 26 undergoing clinical evaluation. This paper aims to review the basics of COVID-19, including epidemiology, basic biology of SARS-CoV-2, and transmission. We also review COVID-19 vaccine development, including animal models, platforms under development, and vaccine development in Canada.

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)0.002
metaresearch head score (Gemma)0.002
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 score0.876
Threshold uncertainty score0.247

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0060.003

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 head0.055
GPT teacher head0.346
Teacher spread0.291 · 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

Citations4
Published2020
Admission routes4
Has abstractyes

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