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Global, regional, and national burden of stroke and its risk factors, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

2024· article· en· W6959478596 on OpenAlexfundno aff

Bibliographic record

VenueRepository@Hull (Worktribe) (University of Hull) · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetic and Environmental Crop Studies
Canadian institutionsnot available
FundersCilagPrecursory Research for Embryonic Science and TechnologyJapan Science and Technology AgencyNovartis PharmaAllerganNational Institutes of HealthEuropean Stroke OrganisationEsperion TherapeuticsNational Science and Technology CouncilDSM Nutritional ProductsIntas PharmaceuticalsLilly DeutschlandNational Research, Development and Innovation OfficeNational Health and Medical Research CouncilNeuraxpharmNovo Nordisk PharmaMinistry of Science and ICT, South KoreaMedical Research CouncilAfrican Academy of SciencesServierIstituto Auxologico ItalianoUniversity of JordanNovo NordiskEisaiConselho Nacional de Desenvolvimento Científico e TecnológicoMinistero della SaluteGeneralitat de CatalunyaMinistry of Education, Culture, Sports, Science and TechnologyAmryt PharmaAustralian Academy of ScienceJohns Hopkins UniversityAmarin CorporationCardinal HealthDaiichi Sankyo EuropeAgios PharmaceuticalsRegeneron PharmaceuticalsFondazione CariploFresenius Medical Care North AmericaDeutsche ForschungsgemeinschaftAlzheimer's AssociationGlobal Brain Health InstituteIdorsia PharmaceuticalsH. Lundbeck A/SInternational Hepato-Pancreato-Biliary AssociationGovernment of CanadaUltragenyx PharmaceuticalCanadian Institutes of Health ResearchItalfarmacoKorean Diabetes AssociationEuropean CommissionAstraZenecaInternational Atomic Energy AgencyAlexion PharmaceuticalsNational Research Foundation of KoreaBiogenKing Saud UniversityBristol-Myers SquibbTeva Pharmaceutical IndustriesAmerican Heart AssociationModernaBill and Melinda Gates FoundationPfizerAmicus TherapeuticsCasen RecordatiAlexander von Humboldt-StiftungJapan Society for the Promotion of ScienceSwedish Orphan BiovitrumAstellas PharmaBayerCardiff UniversityU.S. Department of DefenseEli Lilly and CompanyAOSpineDanoneAmerican Diabetes AssociationSociedad Madrileña de NefrologíaNational Research FoundationAmgenInternational Society of Travel MedicineNational Cerebral and Cardiovascular CenterSanofi
KeywordsStroke (engine)Burden of diseaseDisease burdenAttributable riskQuality-adjusted life yearCause of deathIncidence (geometry)DiseaseDisability-adjusted life year

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.008
Bibliometrics0.0040.010
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.205
Teacher spread0.189 · 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 designMeta-analysis
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
Published2024
Admission routes1
Has abstractno

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