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Record W3116829181 · doi:10.3390/vaccines9010011

Platforms Exploited for SARS-CoV-2 Vaccine Development

2020· review· en· W3116829181 on OpenAlexaff
Shilu Mathew, Muhammed Faheem, Neeraja A. Hassain, Fatiha M. Benslimane, Asmaa A. Al Thani, Hassan Zaraket, Hadi M. Yassine

Bibliographic record

VenueVaccines · 2020
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsHospital for Sick Children
FundersQatar University
KeywordsPandemicCoronavirusVirologyCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)MedicinePopulationIntensive care medicinePublic healthDiseaseImmunologyInfectious disease (medical specialty)Environmental health

Abstract

fetched live from OpenAlex

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the only zoonotic-origin coronavirus (CoV) that has reached the pandemic stage. The virus uses its spike (S) glycoprotein to attach to the host cells and initiate a cascade of events that leads to infection. It has sternly affected public health, economy, education, and social behavior around the world. Several scientific and medical communities have mounted concerted efforts to limit this pandemic and the subsequent wave of viral spread by developing preventative and potential vaccines. So far, no medicine or vaccine has been approved to prevent or treat coronavirus disease 2019 (COVID-19). This review describes the latest advances in the development of SARS-CoV-2 vaccines for humans, mainly focusing on the lead candidates in clinical trials. Moreover, we seek to provide both the advantages and the disadvantages of the leading platforms used in current vaccine development, based on past vaccine delivery efforts for non-SARS CoV-2 infections. We also highlight the population groups who should receive a vaccine against COVID-19 in a timely manner to eradicate the pandemic rapidly.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.959
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.161
GPT teacher head0.416
Teacher spread0.255 · 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

Citations24
Published2020
Admission routes1
Has abstractyes

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