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Record W3009722387 · doi:10.3390/jrfm13030046

Prevention Is Better Than the Cure: Risk Management of COVID-19

2020· article· en· W3009722387 on OpenAlexvenueno aff
Michael McAleer

Bibliographic record

VenueJournal of risk and financial management · 2020
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsnot available
FundersAustralian Research Council
KeywordsPandemicCoronavirus disease 2019 (COVID-19)HeadlineTimelineGlobal healthSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)China2019-20 coronavirus outbreakIndex (typography)CoronavirusDiseaseMedicineGeographyEnvironmental healthOutbreakVirologyBusinessPublic healthInfectious disease (medical specialty)Computer scienceAdvertising

Abstract

fetched live from OpenAlex

A novel coronavirus was reported to the World Health Organization (WHO) in China on 31 December 2019. The WHO named the disease COVID-19 on 11 February 2020. As of 26 February 2020, the disease has been detected on all continents, except for Antarctica. Daily updates on COVID-19 since early February 2020 have made headline news worldwide for much of 2020. This editorial evaluates risk management based on the Global Health Security (GHS) Index of global health security capabilities in 195 countries. The GHS Index lists the countries best prepared for an epidemic or pandemic. COVID-19 is compared with two related coronavirus epidemics, SARS and MERS, in terms of the number of reported human infections, deaths, countries, major country clusters, timelines, and the likelihood of discovering a safe, effective, and approved vaccine.

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)0.013
metaresearch head score (Gemma)0.070
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.013
Threshold uncertainty score0.069

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0130.070
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0050.005
Open science0.0010.001
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0040.001

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 head0.110
GPT teacher head0.364
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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations150
Published2020
Admission routes1
Has abstractyes

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