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Record W1968370982 · doi:10.3934/dcdsb.2002.2.257

A model for an SI disease in an age - structured population

2002· article· en· W1968370982 on OpenAlexaff
Fred Brauer

Bibliographic record

VenueDiscrete and Continuous Dynamical Systems - B · 2002
Typearticle
Languageen
FieldMathematics
TopicCOVID-19 epidemiological studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsLife spanBasic reproduction numberDiseaseDemographyMathematicsExponential distributionExponential growthPopulationInfectious disease (medical specialty)Applied mathematicsStatisticsEconometricsBiologyMedicineEvolutionary biologyMathematical analysisSociologyInternal medicine

Abstract

fetched live from OpenAlex

We formulate and analyze a model for an infectious disease which does notcause death but for which infectives remain infective for life. We derive the basic reproductivenumber $R_0$ and show that there is a unique globally asymptotically stable equilibrium,namely the disease - free equilibrium if $R_0 1$.However, the relation between the basic reproductive number, the mean age at infection,and the mean life span depends on the distribution of life spans and may be quite differentfrom that for exponentially distributed life spans or very short infective periods.

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.

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)0.001
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0020.001
Research integrity0.0030.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.143
GPT teacher head0.372
Teacher spread0.228 · 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

Citations18
Published2002
Admission routes1
Has abstractyes

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Same venueDiscrete and Continuous Dynamical Systems - BSame topicCOVID-19 epidemiological studiesFrench-language works237,207