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Record W4399407934 · doi:10.1016/j.jde.2024.05.049

Spatial dynamics of a generalized cholera model with nonlocal time delay in a heterogeneous environment

2024· article· en· W4399407934 on OpenAlexaff
Wei Wang, Xiaotong Wang, Hao Wang

Bibliographic record

VenueJournal of Differential Equations · 2024
Typearticle
Languageen
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMathematicsDynamics (music)Applied mathematicsCholeraStatistical physicsPhysicsMedicine

Abstract

fetched live from OpenAlex

In this work, we mechanistically formulate a generalized cholera model with nonlocal time delay to study the impact of bacterial hyperinfectivity on cholera epidemics in a spatially heterogeneous environment. Mathematical challenges lie in the fact that (i) the generalized cholera model considers the intrinsic growth of short-lived hyperinfectious (HI vibrios) state of V. cholerae and lower-infectious (LI vibrios) state of V. cholerae simultaneously; and (ii) this article originally derives the detailed classifications of spatial dynamics for the cholera model with some generally functional response functions, non-uniformness of diffusion rates and nonlocal time delay. We introduce three basic reproduction numbers: one is for HI state of V. cholerae , the other is for LI state of V. cholerae , and another is for the cholera disease in the host population. Based on these basic reproduction numbers, we further establish the global threshold dynamics. Under some conditions, the basic reproduction number of infection is strictly decreasing with respect to the diffusion coefficients of infectious hosts.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.729
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.018
GPT teacher head0.266
Teacher spread0.248 · 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 teacher head, 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

Citations13
Published2024
Admission routes1
Has abstractyes

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