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Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010
Rafael Lozano, Mohsen Naghavi, Kyle J Foreman, Stephen S Lim, Kenji Shibuya, Victor Aboyans, Jerry Abraham, Tim Adair, Rakesh Aggarwal, Stephanie Y Ahn, Mohammad A. AlMazroa, Miriam Alvarado, H Ross Anderson, Laurie Anderson, Kathryn Andrews, Charles Atkinson, Larry M. Baddour, Suzanne Barker‐Collo, David Bartels, Michelle L. Bell, Emelia J. Benjamin, Derrick Bennett, Kavi Bhalla, Boris Bikbov, Aref Bin Abdulhak, Gretchen L. Birbeck, Fiona Blyth, Ian Bolliger, Soufiane Boufous, Chiara Bucello, Michael Burch, Peter Burney, Jonathan R. Carapetis, Honglei Chen, David Chou, Sumeet S. Chugh, Luc E. Coffeng, Steven D Colan, Samantha Colquhoun, K. Ellicott Colson, John R. Condon, Myles Connor, Leslie T. Cooper, Matthew Corriere, Monica Cortinovis, William Couser, Michael H Criqui, Marita Cross, Kaustubh Dabhadkar, Nabila Dahodwala, Diego De Leo, Louisa Degenhardt, Allyne Delossantos, Julie O. Denenberg, Don C. Des Jarlais, Samath Dhamminda Dharmaratne, E. Ray Dorsey, Tim Driscoll, Herbert C. Duber, Beth E. Ebel, Patricia J. Erwin, Patricia Espindola, Majid Ezzati, Valery L. Feigin, Abraham D Flaxman, Mohammad H. Forouzanfar, F.G.R. Fowkes, Richard C. Franklin, Marlene Fransen, Michael K Freeman, Sherine E. Gabriel, Emmanuela Gakidou, Flavio Gaspari, Richard F Gillum, Diego González-Medina, Yara A. Halasa, Diana Haring, James Harrison, Rasmus Havmoeller, Roderick J. Hay, Bruno Hoen, Peter J. Hotez, Damian Hoy, Kathryn H. Jacobsen, Spencer L James, Rashmi Jasrasaria, Sudha Jayaraman, Nicole E. Johns, Ganesan Karthikeyan, Nicholas J Kassebaum, Andre Keren, Jon‐Paul Khoo, Lisa Marie Knowlton, Olive Kobusingye, Adofo Koranteng, Rita Krishnamurthi, Michael S. Lipnick, Steven E. Lipshultz, Summer Lockett Ohno, Jacqueline Mabweijano, Michael F MacIntyre, Leslie Mallinger, Lyn March, Guy B. Marks, Robin Marks, Akira Matsumori, Richard Matzopoulos, Bongani M. Mayosi, John H. McAnulty, Mary Mcdermott, John McGrath, Ziad A. Memish, George A. Mensah, Tony R. Merriman, Catherine Michaud, Matthew Miller, Ted R. Miller, Charles Mock, Ana Olga Mocumbi, Ali A. Mokdad, Andrew Moran, Kim Mulholland, M Nathan Nair, Luigi Naldi, K M Venkat Narayan, Kiumarss Nasseri, Paul E. Norman, Martin O’Donnell, Saad B Omer, Katrina Ortblad, Richard H. Osborne, Doruk Ozgediz, Bishnu Pahari, Jeyaraj Pandian, Andrea Panozo Rivero, Rogelio Perez Padilla, Fernando Pérez-Ruiz, Norberto Perico, David Phillips, Kelsey Pierce, C Arden Pope, Esteban Porrini, Farshad Pourmalek, Murugesan Raju, Dharani Ranganathan, Jürgen T Rehm, David B. Rein, Frederick P Rivara, Thomas Roberts, Felipe Rodriguez De León, Lisa C Rosenfeld, Lesley Rushton, Ralph L Sacco, Joshua A. Salomon, Uchechukwu K.A. Sampson, Ella Sanman, David C. Schwebel, María Seguí‐Gómez, Donald S. Shepard, David Singh, Jessica Singleton, Karen Sliwa, Emma Smith, Andrew C. Steer, Jennifer A Taylor, Bernadette Thomas, Jeffrey A Towbin, Thomas Truelsen, Eduardo A. Undurraga, Narayanaswamy Venketasubramanian, Lakshmi Vijayakumar, Theo Vos, Gregory R. Wagner, Mengru Wang, Wenzhi Wang, Kerrianne Watt, Martin A. Weinstock, Robert Weintraub, James D. Wilkinson, Anthony D. Woolf, Sarah Wulf, Pon-Hsiu Yeh, Paul Yip, Azadeh Zabetian, Zhijie Zheng, Alan D López, Christopher J L Murray
Bibliographic record
VenueThe Lancet · 2012
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsCentre for Addiction and Mental HealthUniversity of British Columbia
FundersNational Institute on AgingNational Drug and Alcohol Research CentreHealth Research Council of New ZealandNational Health and Medical Research CouncilMedical Research CouncilCenters for Disease Control and PreventionNational Institutes of HealthWorld Heart FederationUniversity of New South WalesH. Lundbeck A/SNational Heart, Lung, and Blood InstituteInstitute for Health Metrics and EvaluationVetenskapsrådetBill and Melinda Gates FoundationRobert Wood Johnson FoundationUniversity of SydneyWorld Health OrganizationVanderbilt UniversityLomonosov Moscow State UniversityPepsiCo
KeywordsCovariateCause of deathDemographyMedicineStatisticsMissing dataDiseaseMathematics
Abstract
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 imitationNot 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)0.003
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: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.105
Threshold uncertainty score0.210
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.011 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 head0.068
GPT teacher head0.350
Teacher spread0.282 · how far apart the two teachers sit on this one work
Validation status
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine 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
Citations14,264
Published2012
Admission routes1
Has abstractno