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Record W2087102697 · doi:10.1142/s1793524509000790

STRUCTURED INFLUENZA MODEL FOR META-POPULATION

2009· article· en· W2087102697 on OpenAlex
Marija Zivkovic Gojovic, Dong Liang

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInternational Journal of Biomathematics · 2009
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsYork University
FundersMitacs
KeywordsPandemicDiseaseComputer sciencePopulationDisease controlControl (management)Epidemic diseaseEpidemic modelCoronavirus disease 2019 (COVID-19)Operations researchEconometricsDemographyMedicineMathematicsEnvironmental healthArtificial intelligenceVirologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

We present a mathematical model parameterized to simulate the 1918 pandemic and modified to account for today's achievements in medical care and technology. Our goal is to use the model with carefully selected parameters to analyze and simulate different scenarios in a changing environment including behavior changes and reduction of mobility as the disease progresses. The model is structured by the disease age, representing the time elapsed since the exposure to influenza infection, and most of the parameters used in this study are thus disease-age dependent. We also consider the case where an influenza pandemic affects two distinct regions, connected only through controlled mobility. We evaluate the influence of different control measures on temporal patterns of disease dynamics and consider the impact of the movement of disease age structured population on spatial spread. A special example is examined that considers different scenarios of disease spread between Canada and USA when different border control strategies are implemented.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

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)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.509
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.457
GPT teacher head0.508
Teacher spread0.051 · 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