MétaCan
Menu
Back to cohort
Record W4412430602 · doi:10.1016/j.chaos.2025.116708

Stability analysis and bifurcations of a modified Nicholson–Bailey type model

2025· article· en· W4412430602 on OpenAlexaff
Sultanah Masmali, Reza GhamarShoushtari, Majid Jaberi‐Douraki

Bibliographic record

VenueChaos Solitons & Fractals · 2025
Typearticle
Languageen
FieldMathematics
TopicAdvanced Differential Equations and Dynamical Systems
Canadian institutionsUniversité de Sherbrooke
FundersKansas State University
KeywordsType (biology)MathematicsStability (learning theory)Applied mathematicsCalculus (dental)Mathematical analysisComputer scienceGeologyMedicine

Abstract

fetched live from OpenAlex

In this paper, we investigate the dynamical behavior of a host-parasite model through the modification of a Nicholson–Bailey (MNB) model that contains four biological parameters in the first closed quadrant. By a re-scaling procedure, the MNB model is then reduced to a two-parameter system that almost entirely carries over the comprehensive dynamics of the original model. The new model always possesses two boundary steady states and we show that a third and unique interior steady state may exist under certain conditions imposed on one of the parameters. We then analyze the local stability of each steady state for a different range of parameters by the linearization process of the model about each steady state. For specific values of the parameters in which a steady state is non-hyperbolic, the stability and dynamics of the steady state are studied by the application of bifurcation identities developed from the center manifold theory. Moreover, using linearized stability function, we find thresholds for which the system is stable or unstable. We eventually study the local stability analysis of a period-doubling bifurcation which may occur once we cross one of these thresholds, implying irregular dynamics which may lead to chaos. The results are supported by some simulations.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.533

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.066
GPT teacher head0.368
Teacher spread0.302 · 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 designTheoretical or conceptual
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

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueChaos Solitons & FractalsSame topicAdvanced Differential Equations and Dynamical SystemsFrench-language works237,207