Record W7073817382

Global, regional, and national incidence of six major immune-mediated inflammatory diseases : findings from the global burden of disease study 2019

2023· other· en· W7073817382 on OpenAlexfundno aff

Bibliographic record

VenuePortuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT) · 2023

Typeother

Languageen

FieldEarth and Planetary Sciences

TopicSeismic Imaging and Inversion Techniques

Canadian institutionsnot available

FundersEuropean and Developing Countries Clinical Trials PartnershipNational Research, Development and Innovation OfficeNational Health and Medical Research CouncilUniversity at BuffaloMedical Research CouncilDebre Tabor UniversityUniversity of Health and Allied SciencesMadda Walabu UniversityUniversitas PadjadjaranINCLIVA Instituto de Investigación SanitariaUniversity of ZanjanUniversity of Agriculture, FaisalabadYasuj University of Medical SciencesCentro de Investigación Biomédica en Red de Salud MentalCentre Hospitalier Universitaire VaudoisShahid Beheshti University of Medical SciencesUniversity of GondarUniversità degli Studi del Piemonte OrientaleInstituto de Salud Carlos IIIShiraz UniversityJimma UniversityShahrekord UniversityAhvaz Jundishapur University of Medical SciencesChinese University of Hong KongMinisterio de Ciencia e InnovaciónTaipei Medical UniversityKerman University of Medical SciencesTehran University of Medical Sciences and Health ServicesSultan Qaboos UniversityIslamic Azad University, ShahrekordShiraz University of Medical SciencesDirectorate for Biological SciencesKing Abdulaziz UniversityJordan University of Science and TechnologyIsfahan University of Medical SciencesScience and Technology Development FundUniversity of PretoriaIslamic Azad UniversityFlinders UniversityCairo UniversityUniversité de Versailles Saint-Quentin-en-YvelinesUniversity of CanberraUniversity of TorontoZanjan University of Medical SciencesStockholms Läns LandstingUniversity of New South WalesPublic Health AgencyAmity UniversityKing Faisal UniversityNational Institute for Health and Care ResearchMinistero della SaluteHarvard UniversityAsian Institute of Medicine, Science and TechnologyIndian Council of Medical ResearchCancer Institute NSWSocial Science Research CouncilUniversity of TsukubaUniversità di CataniaSRM Institute of Science and TechnologyBelgian American Educational FoundationLa Trobe UniversityArabian Gulf UniversityManchester Biomedical Research CentreUniversity of Electronic Science and Technology of ChinaMonash UniversitySouth Eastern Sydney Local Health DistrictShaqra UniversityIran University of Medical SciencesHorizon 2020 Framework ProgrammeShahid Sadoughi University of Medical SciencesUniversitatea de Medicină şi Farmacie "Carol Davila" BucureştiAcademy of Scientific Research and TechnologyUniversity College CorkJazan UniversityLung Foundation AustraliaUniversität BaselEast Carolina UniversityShahrekord University of Medical SciencesRafsanjan University of Medical SciencesPublic Health Agency of CanadaAlborz University of Medical SciencesAin Shams UniversityCleveland ClinicMashhad University of Medical SciencesPublic Health Foundation of IndiaCleveland Clinic FoundationVirginia Commonwealth UniversityNational Nutrition and Food Technology Research InstituteKasturba Medical College, ManipalUniversidade de São PauloKrishna Institute Of Medical Sciences Deemed To Be UniversityUniversity of Nevada, Las VegasZagazig UniversityCharles Sturt UniversityUniversity of SydneyUniversity of Southern CaliforniaBill and Melinda Gates Foundation

KeywordsIncidence (geometry)Rheumatoid arthritisAsthmaAtopic dermatitisInflammatory bowel diseasePsoriasis

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 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)0.004

Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated

Candidate categoriesScience and technology studies

Consensus categoriesnone

DomainCandidate signal: none · Consensus signal: none

Study designCandidate signal: Observational · Consensus signal: Observational

GenreCandidate signal: Empirical · Consensus signal: Empirical

Teacher disagreement score0.284

Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

Category	Codex	Gemma
Metaresearch	0.003	0.004
Meta-epidemiology (narrow)	0.000	0.000
Meta-epidemiology (broad)	0.000	0.000
Bibliometrics	0.001	0.003
Science and technology studies	0.001	0.004
Scholarly communication	0.000	0.000
Open science	0.001	0.000
Research integrity	0.000	0.000
Insufficient payload (model declined to judge)	0.000	0.000

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 head0.035

GPT teacher head0.332

Teacher spread0.297 · 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