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Record W1494204496 · doi:10.1016/s0140-6736(12)61680-8

Common values in assessing health outcomes from disease and injury: disability weights measurement study for the Global Burden of Disease Study 2010

2012· article· en· W1494204496 on OpenAlexaff
Joshua A. Salomon, Theo Vos, Daniel Hogan, Michaël Gagnon, Mohsen Naghavi, Nazma Begum, Razibuzzaman Shah, Muhammad Karyana, Soewarta Kosen, Mario Reyna Farje, Gilberto Moncada, Arup Dutta, Sunil Sazawal, Andrew R. Dyer, Jana Seiler, Victor Aboyans, Emelia J. Benjamin, Kavi Bhalla, Aref Bin Abdulhak, Fiona Blyth, Rupert Bourne, Tasanee Braithwaite, Peter Brooks, Traolach Brugha, Claire Bryan-Hancock, Rachelle Buchbinder, Peter Burney, Bianca Calabria, Sumeet S. Chugh, Rebecca Smith Cooley, Michael H Criqui, Marita Cross, Kaustubh Dabhadkar, Nabila Dahodwala, A. C. J. Davis, Louisa Degenhardt, Cèsar Díaz‐Torné, E. Ray Dorsey, Tim Driscoll, Karen Edmond, Valery L. Feigin, Cleusa P. Ferri, Abraham D Flaxman, Louise Flood, Kana Fuse, Belinda J. Gabbe, Richard F Gillum, J Haagsma, James Harrison, Rasmus Havmoeller, Roderick J. Hay, Abdullah Hel-Baqui, Hans W. Hoek, Howard J. Hoffman, Emily W. Hogeland, Damian Hoy, Deborah Jarvis

Bibliographic record

VenueThe Lancet · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsCentre for Addiction and Mental HealthUniversity of British Columbia
FundersNational Institute on AgingMedical Research CouncilFoundation for Alcohol Research and EducationUniversitair Medisch Centrum GroningenDepartment of Health, State Government of VictoriaSociedad Española de ReumatologíaUniversidad de NavarraFlinders UniversityNational Institutes of HealthUniversity of LeicesterNational Institute for Health and Care ResearchHarvard Global Health InstituteNational Heart, Lung, and Blood InstituteVetenskapsrådetAustralian GovernmentWellcome TrustVanderbilt UniversityAnglia Ruskin UniversityMonash UniversityNational Health and Medical Research CouncilBupa FoundationRobert Wood Johnson FoundationBill and Melinda Gates Foundation
KeywordsMedicinePublic healthDisease burdenPopulationGerontologyBurden of diseaseDiseaseGlobal healthDisability-adjusted life yearEnvironmental healthPsychologyNursing

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)0.057
metaresearch head score (Gemma)0.090
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.057
Threshold uncertainty score0.301

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0570.090
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0050.011
Science and technology studies0.0020.001
Scholarly communication0.0030.004
Open science0.0020.006
Research integrity0.0020.004
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 head0.475
GPT teacher head0.487
Teacher spread0.011 · 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

Citations104
Published2012
Admission routes1
Has abstractno

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Same venueThe LancetSame topicHealth Systems, Economic Evaluations, Quality of LifeFrench-language works237,207