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Record W3127688953 · doi:10.1096/fj.202002662r

COVID‐19: Current knowledge in clinical features, immunological responses, and vaccine development

2021· review· en· W3127688953 on OpenAlexafffund
Ramandeep Singh, Alisha Kang, Xiang‐Qian Luo, Mangalakumari Jeyanathan, Amy Gillgrass, Sam Afkhami, Zhou Xing

Bibliographic record

VenueThe FASEB Journal · 2021
Typereview
Languageen
FieldMedicine
TopicSARS-CoV-2 and COVID-19 Research
Canadian institutionsMcMaster University
FundersCanadian Institutes of Health Research
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)VirologyImmunizationGlobal healthMedicine2019-20 coronavirus outbreakImmunologyIntensive care medicinePublic healthImmune systemInfectious disease (medical specialty)DiseaseOutbreak

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has unfolded to be the most challenging global health crisis in a century. In 11 months since its first emergence, according to WHO, the causative infectious agent SARS-CoV-2 has infected more than 100 million people and claimed more than 2.15 million lives worldwide. Moreover, the world has raced to understand the virus and natural immunity and to develop vaccines. Thus, within a short 11 months a number of highly promising COVID-19 vaccines were developed at an unprecedented speed and are now being deployed via emergency use authorization for immunization. Although a considerable number of review contributions are being published, all of them attempt to capture only a specific aspect of COVID-19 or its therapeutic approaches based on ever-expanding information. Here, we provide a comprehensive overview to conceptually thread together the latest information on global epidemiology and mitigation strategies, clinical features, viral pathogenesis and immune responses, and the current state of vaccine development.

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)0.007
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.991
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.006
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 head0.212
GPT teacher head0.497
Teacher spread0.286 · 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 designOther design
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

Citations96
Published2021
Admission routes2
Has abstractyes

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