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Record W2037213314 · doi:10.1017/s0308210500002523

Extinction and wavefront propagation in a reaction-diffusion model of a structured population with distributed maturation delay

2003· article· en· W2037213314 on OpenAlexaff
Stephen A. Gourley, J. W.-H. So

Bibliographic record

VenueProceedings of the Royal Society of Edinburgh Section A Mathematics · 2003
Typearticle
Languageen
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExtinction (optical mineralogy)Zero (linguistics)MathematicsWavefrontPopulationFunction (biology)Probability density functionStatistical physicsDistribution (mathematics)DiffusionPartial differential equationReaction–diffusion systemDomain (mathematical analysis)Applied mathematicsMathematical analysisPhysicsStatisticsDemographyThermodynamics

Abstract

fetched live from OpenAlex

Starting from an age-structured model, we derive a partial differential equation satisfied by the total number of mature adult members of a population, on an infinite one-dimensional domain. The formulation involves a distribution of possible ages of maturation and uses a probability density function on which ecologically realistic assumptions are made. It is found that the existence and value of a positive equilibrium solution depends on the mean maturation delay. When no positive equilibrium exists, we prove global attractivity of the zero solution. For a particular ecologically reasonable choice of the distribution function, we show that travelling fronts exist connecting the zero equilibrium with the positive one provided the mean maturation delay is sufficiently small, and the dependence of the front's propagation speed on the mean delay is discussed.

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)0.003
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 score0.013
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
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 head0.013
GPT teacher head0.235
Teacher spread0.221 · 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

Citations39
Published2003
Admission routes1
Has abstractyes

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Same venueProceedings of the Royal Society of Edinburgh Section A MathematicsSame topicMathematical and Theoretical Epidemiology and Ecology ModelsFrench-language works237,207