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Record W6931180039 · doi:10.5281/zenodo.3755889

Risk factors of ishemic stroke and their interconnection

2020· dissertation· en· W6931180039 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2020
Typedissertation
Languageen
FieldNeuroscience
TopicNeurological Disorders and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsStroke (engine)Risk factorIschemic strokeDiseaseEpidemiologyVascular disease

Abstract

fetched live from OpenAlex

1. Thesis, тезисы In English: [Mishchenko, M.M., Shevchenko, A.S., Mishchenko, A.N. (2020) Risk factors of ishemic stroke and their interconnection. Dynamics of the development of world science: Abstracts of the 8th International scientific and practical conference (Vancouver, Canada, 2020, April 15-17). Publishing House “ACCENT” (ISBN 978-1-4879-3791-1). Pp. 124-129. https://doi.org/10.5281/zenodo.3755806] Cardiovascular disease is the leading cause of premature death. In turn, among cardiovascular diseases, the leader is ischemic stroke. The main risk factors for ischemic strokes (behavioral, physiological, genetic, environmental) act synergistically and are pathogenetically interconnected. Keywords: cardiovascular diseases, ischemic stroke, risk factors, age factor, hypodynamia, hypercholesterolemia, hyperglycemia, diabetes, obesity, overeating, salt, alcohol, tobacco smoking, arterial hypertension, atrial fibrillation, vascular atherosclerosis, environmental burden. На русском: [Мищенко, М.М., Шевченко, А.С., Мищенко, А.Н. (2020) Факторы риска ишемического инсульта и их взаимосвязь. Динамика развития современной науки: Тезисы докладов 8-й Международной научно-практической конференции (Ванкувер, Канада, 2020, 15-17 апреля). Издательский дом «АКЦЕНТ» (ISBN 978-1-4879-3791-1). C. 124-129. https://doi.org/10.5281/zenodo.3755806 (На английском)] Сердечно-сосудистые заболевания лидируют среди причин преждевременных смертей. В свою очередь среди сердечно-сосудистых заболеваний лидером является ишемический инсульт. Главные факторы риска ишемических инсультов (поведенческие, физиологические, генетические, экологические) действую синергетично и взаимосвязаны патогенетически. Ключевые слова: сердечно-сосудистые заболевания, ишемический инсульт, факторы риска, фактор возраста, гиподинамия, гиперхолестеринемия, гипергликемия, диабет, ожирение, переедание, поваренная соль, алкоголь, табакокурение, артериальная гипертензия, мерцательная аритмия, атеросклероз сосудов, экологическое бремя. 2. Certificates of conference participants

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.011
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.038
GPT teacher head0.248
Teacher spread0.210 · 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 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
Published2020
Admission routes1
Has abstractyes

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