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Record W3089283915 · doi:10.1016/j.onehlt.2020.100174

Unexpected positive correlation between human development index and risk of infections and deaths of COVID-19 in Italy

2020· article· en· W3089283915 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueOne Health · 2020
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsHuman Development IndexCase fatality rateCoronavirus disease 2019 (COVID-19)DemographyIndex (typography)PopulationCorrelationMedicineDiseaseEnvironmental healthHuman development (humanity)Infectious disease (medical specialty)Internal medicineMathematics

Abstract

fetched live from OpenAlex

In this analysis, we observed that human development index (an integrated index of life expectation, education and living standard) correlates with infection rate (proportion of confirmed cases among the population) and the fatality rate of COVID-19 in Italy based on data as of May 15, 2020. Further analysis showed that HDI is negatively correlated with cigarette consumption, whereas it is positively correlated with chronic disease and average annual gross salary. These factors may partially explain why unexpected positive correlation is observed between human development index and risk of infections and deaths of COVID-19 in Italy.

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.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.015
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.236
GPT teacher head0.437
Teacher spread0.201 · 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