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Record W2044591518 · doi:10.1371/journal.pmed.1001558

Global Mortality Estimates for the 2009 Influenza Pandemic from the GLaMOR Project: A Modeling Study

2013· article· en· W2044591518 on OpenAlexfundno aff
Lone Simonsen, Peter Spreeuwenberg, Roger Lustig, Robert J. Taylor, Douglas Fleming, Madelon Kroneman, Maria D. Van Kerkhove, Anthony W. Mounts, W J Paget

Bibliographic record

VenuePLoS Medicine · 2013
Typearticle
Languageen
FieldMedicine
TopicInfluenza Virus Research Studies
Canadian institutionsnot available
FundersFogarty International CenterStatens Serum InstitutRijksinstituut voor Volksgezondheid en MilieuMedical Research CouncilRobert Koch InstitutNational Institutes of HealthChinese Center for Disease Control and PreventionArizona State UniversityNSW Ministry of HealthNederlands Instituut voor Onderzoek van de GezondheidszorgPublic Health EnglandUniversity of New South WalesUniversity of OtagoKoch Institute for Integrative Cancer Research, Massachusetts Institute of TechnologyInstituto de Salud Carlos IIINational University of SingaporePublic Health Agency of CanadaPan American Health OrganizationCenters for Disease Control and PreventionKeiyu HospitalEuropean Centre for Disease Prevention and ControlNational Health Laboratory ServiceKorea Centers for Disease Control and PreventionInstitut National de la Santé et de la Recherche MédicaleBill and Melinda Gates FoundationAssistance publique-Hôpitaux de ParisGeorge Washington UniversityUniversity of Hong KongPublic Health AgencyScience and Technology DirectorateU.S. Department of Homeland Security
KeywordsPandemicDemographyMortality ratePopulationMedicinePublic healthGlobal healthInfluenza pandemicEnvironmental healthGeographyCoronavirus disease 2019 (COVID-19)Infectious disease (medical specialty)Disease

Abstract

fetched live from OpenAlex

OpenAlex records an abstract for this work, but it could not be fetched just now.

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)0.004
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 score0.037
Threshold uncertainty score0.073

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.002
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.309
GPT teacher head0.463
Teacher spread0.154 · 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

Citations500
Published2013
Admission routes1
Has abstractyes

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