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Record W2775569101 · doi:10.1016/s0140-6736(17)33293-2

Estimates of global seasonal influenza-associated respiratory mortality: a modelling study

2017· article· en· W2775569101 on OpenAlexaff
A. Danielle Iuliano, Katherine Roguski, Howard H. Chang, David Muscatello, Rakhee Palekar, Stefano Tempia, Cheryl Cohen, Jon Michael Gran, Dena L. Schanzer, Benjamin J. Cowling, Peng Wu, Jan Kynčl, Li Wei Ang, Minah Park, Monika Redlberger‐Fritz, Hongjie Yu, Laura Espenhain, Anand Krishnan, Gideon O. Emukule, Liselotte van Asten, Susana Pereira Silva, Suchunya Aungkulanon, Udo Buchholz, Marc‐Alain Widdowson, Joseph Bresee, Eduardo Azziz‐Baumgartner, Po‐Yung Cheng, Fatimah S. Dawood, Ivo Foppa, Sonja J. Olsen, Michael Haber, Caprichia Jeffers, C. Raina MacIntyre, Anthony T. Newall, James Wood, Michael Kundi, Therese Popow‐Kraupp, Makhdum Ahmed, Mahmudur Rahman, C Viviana Sotomayor Proschle, Natalia Vergara Mallegas, Sa Li, Juliana Barbosa-Ramírez, Diana Malo Sanchez, Leandra Abarca Gómez, Xiomara Badilla Vargas, aBetsy Acosta Herrera, María Josefa Llanés, Thea Kølsen Fischer, Tyra Grove Krause, Kåre Mølbak, Jens Nielsen, Ramona Trebbien, Alfredo Bruno, Jenny Ojeda, Héctor Romero Ramos, Matthias an der Heiden, Leticia del Carmen Castillo Signor, Carlos Enrique Lemus Serrano, Rohit Bhardwaj, Mandeep Chadha, Venkatesh Vinayak Narayan, Soewarta Kosen, Michal Bromberg, Aharona Glatman‐Freedman, Zalman Kaufman, Yuzo Arima, Kazunori Oishi, Sandra S. Chaves, Bryan O. Nyawanda, Reem Abdullah Al-Jarallah, Pablo Kuri‐Morales, Cuitláhuac Ruiz Matus, María Eugenia Jiménez Corona, Burmaa Alexander, Oyungerel Darmaa, Majdouline Obtel, Imad Cherkaoui, Cees C. van den Wijngaard, Wim van der Hoek, Michael G. Baker, Don Bandaranayake, Ange Bissielo, Liza Lopez, Elmira Flem, Gry Marysol Grøneng, Siri Helene Hauge, Federico G. de Cosío, Yadira Moltó, Lourdes Moreno Castillo, María Águeda Cabello, Ausenda Machado, Baltazar Nunes, Ana Paula Rodrigues, Emanuel Rodrigues, Cristian Calomfirescu, Emilia Lupulescu, Rodica Popescu, Odette Popovici, Dragan Bogdanović, Marina Kostić, Konstansa Lazarević, Zoran Milošević, Branislav Tiodorović, Mark Chen, Jeffery Cutter, Vernon Lee, Raymond Tzer Pin Lin, Stefan Ma, Adam L. Cohen, Florette K. Treurnicht, Woo Joo Kim, Salvador de Mateo Ontañón, Amparo Larrauri, Inmaculada León-Gómez, Fernando Vallejo, Rita Born, Christoph Junker, Daniel Koch, Jen-Hsiang Chuang, Wan‐Ting Huang, Hung-Wei Kuo, Yi-Chen Tsai, Kanitta Bundhamcharoen, Malinee Chittaganpitch, Helen K. Green, Richard Pebody, Natalia Goñi, Héctor Chiparelli, Lynnette Brammer, Desiree Mustaquim

Bibliographic record

VenueThe Lancet · 2017
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsPublic Health Agency of Canada
FundersNational Institute of General Medical SciencesCenters for Disease Control and PreventionNational Institutes of HealthGAVI Alliance
KeywordsSeasonal influenzaRespiratory systemMedicineVirologyEnvironmental healthCoronavirus disease 2019 (COVID-19)Internal medicineInfectious disease (medical specialty)

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)0.005
metaresearch head score (Gemma)0.010
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 score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.010
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.308
GPT teacher head0.470
Teacher spread0.162 · 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

Citations3,032
Published2017
Admission routes1
Has abstractno

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