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Record W4366811010 · doi:10.3934/mbe.2023486

Dynamic behaviors of a Leslie-Gower model with strong Allee effect and fear effect in prey

2023· article· en· W4366811010 on OpenAlexaff
Zhenliang Zhu, Yuming Chen, Zhong Li, Fengde Chen

Bibliographic record

VenueMathematical Biosciences & Engineering · 2023
Typearticle
Languageen
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsAllee effectBogdanov–Takens bifurcationHopf bifurcationMathematicsLimit cycleBifurcationAttractorHeteroclinic bifurcationBiological applications of bifurcation theoryHomoclinic bifurcationSaddle-node bifurcationLimit (mathematics)Degenerate energy levelsHomoclinic orbitPitchfork bifurcationApplied mathematicsMathematical analysisPhysicsNonlinear systemPopulationDemography

Abstract

fetched live from OpenAlex

We incorporate the strong Allee effect and fear effect in prey into a Leslie-Gower model. The origin is an attractor, which implies that the ecological system collapses at low densities. Qualitative analysis reveals that both effects are crucial in determining the dynamical behaviors of the model. There can be different types of bifurcations such as saddle-node bifurcation, non-degenerate Hopf bifurcation with a simple limit cycle, degenerate Hopf bifurcation with multiple limit cycles, Bogdanov-Takens bifurcation, and homoclinic bifurcation.

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)0.001
metaresearch head score (Gemma)0.001
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: Empirical
Teacher disagreement score0.924
Threshold uncertainty score0.432

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.010
GPT teacher head0.274
Teacher spread0.264 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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