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Record W4281686196 · doi:10.53730/ijhs.v6ns3.8160

Analytical study of the relationship between lifestyle and biological, mental, and social health during the corona in selected countries

2022· article· en· W4281686196 on OpenAlexaff
Hossein Aboozari, Gholamali Afrooz, Parvane Rashidpour, SeyedSaeid SajjadiAnari

Bibliographic record

VenueInternational Journal of Health Sciences · 2022
Typearticle
Languageen
FieldPsychology
TopicCOVID-19 and Mental Health
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMental healthPandemicPsychologyQuarantinePublic healthPolitical scienceEconomic growthCoronavirus disease 2019 (COVID-19)Environmental healthDiseasePublic relationsDevelopment economicsMedicinePsychiatryInfectious disease (medical specialty)NursingEconomics

Abstract

fetched live from OpenAlex

Human beings can no longer continue their former lives due to coronavirus as a new, absolutely unknown, and complex disease. Nowadays, lifestyle and related behaviors have become increasingly important, and the effect of lifestyle-related behaviors on the health of individuals and society emphasizes this importance. This study investigated the relationship between lifestyle and biological, mental, and social health during the corona in selected countries. There was a significant concern in the community in the early stages of the pandemic. Billions of people worldwide used quarantine and social distance to minimize virus transmission. Governments alone cannot relieve the situation. It is necessary to implement a joint effort of support and empathy from citizens, NGOs, public health professionals, and investors to cope with this crisis. This study discussed comparing lifestyle with biological, mental, and social health in different countries and cultures during the corona what differs this study from other studies.

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)0.003
metaresearch head score (Gemma)0.000
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 score0.038
Threshold uncertainty score0.742

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.174
GPT teacher head0.490
Teacher spread0.316 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2022
Admission routes1
Has abstractyes

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