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Record W3120410129 · doi:10.1161/strokeaha.120.032070

Effects of Life Events and Social Isolation on Stroke and Coronary Heart Disease

2021· article· en· W3120410129 on OpenAlexaff
Janine Gronewold, Miriam Engels, Sarah Van de Velde, Thomas Cudjoe, Ela-Emsal Duman, Martha Jokisch, Christoph Kleinschnitz, Karl W. Lauterbach, Raimund Erbel, Karl‐Heinz Jöckel, Dirk M. Hermann

Bibliographic record

VenueStroke · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsInstitute of Health Economics
FundersNational Institute on Aging
KeywordsSocial isolationMedicineDiseaseIsolation (microbiology)Social distancePandemicVulnerability (computing)Stroke (engine)GerontologyCoronavirus disease 2019 (COVID-19)Internal medicineInfectious disease (medical specialty)PsychiatryBioinformatics

Abstract

fetched live from OpenAlex

The current coronavirus disease 2019 (COVID-19) pandemic represents a severe, life-changing event for people across the world. Life changes may involve job loss, income reduction due to furlough, death of a beloved one, or social stress due to life habit changes. Many people suffer from social isolation due to lockdown or physical distancing, especially those living alone and without family. This article reviews the association of life events and social isolation with cardiovascular disease, assembling the current state of knowledge for stroke and coronary heart disease. Possible mechanisms underlying the links between life events, social isolation, and cardiovascular disease are outlined. Furthermore, groups with increased vulnerability for cardiovascular disease following life events and social isolation are identified, and clinical implications of results are presented.

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)0.000
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 score0.010
Threshold uncertainty score0.224

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.311
Teacher spread0.295 · 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

Citations46
Published2021
Admission routes1
Has abstractyes

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