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Record W6989809311

Burden of disease scenarios for 204 countries and territories, 2022–2050 : a forecasting analysis for the Global Burden of Disease Study 2021

2024· article· en· W6989809311 on OpenAlexfundno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicHealth disparities and outcomes
Canadian institutionsnot available
FundersBiotechnology Industry Research Assistance CouncilScience and Engineering Research BoardMedical Research CouncilRede de Química e TecnologiaIdorsia PharmaceuticalsDepartment of Science and Technology, Ministry of Science and Technology, IndiaH. Lundbeck A/SFondation BotnarNational Research FoundationNational Institute for Health and Care ResearchThe Wellcome Trust DBT India AllianceDeutsche ForschungsgemeinschaftSvenska LäkaresällskapetUniversidade do PortoMinistério da Ciência, Tecnologia e Ensino SuperiorWellcome TrustMinistry of Science and ICT, South KoreaNovo NordiskBiogenHjärt-LungfondenNational Institutes of HealthConquer Cancer FoundationKorea Institute for Advancement of TechnologyConselho Nacional de Desenvolvimento Científico e TecnológicoNational Research Foundation of KoreaIndian Council of Medical ResearchMinistry of EducationDepartment of Biotechnology, Ministry of Science and Technology, IndiaAstraZenecaEuropean CommissionUniversidade Nova de LisboaAlexander von Humboldt-StiftungAmicus TherapeuticsUniversity of OxfordFresenius Medical Care North AmericaSt. Jude Children's Research HospitalNational Institute of Mental Health and NeurosciencesJapan Society for the Promotion of ScienceLaboratório Associado para a Química VerdeAstellas PharmaWorld Cancer Research FundGilead SciencesInternational Association for Suicide PreventionWorld Health OrganizationCanadian Institutes of Health ResearchKorean Diabetes AssociationBloomberg PhilanthropiesBundesministerium für Bildung und ForschungAlexion PharmaceuticalsNational Institute of Mental HealthMinisterul Cercetării, Inovării şi DigitalizăriiInternational Parkinson and Movement Disorder SocietyAmerican Diabetes AssociationApplied Molecular Biosciences UnitMinistry of Trade, Industry and EnergySanofiFundação para a Ciência e a TecnologiaBill and Melinda Gates FoundationAmgen
KeywordsBurden of diseaseLife expectancyDisease burdenDiseasePublic healthQuality-adjusted life yearDisability-adjusted life yearRisk factor
DOInot available

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.115
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.003
Science and technology studies0.0000.000
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.074
GPT teacher head0.420
Teacher spread0.347 · 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 designSimulation or modeling
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

Explore more

Same venuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT)→Same topicHealth disparities and outcomes→French-language works237,207→