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Record W2951932242 · doi:10.1063/1.5096661

Multistability driven by inhibitory kinetics in a discrete-time size-structured chemostat model

2019· article· en· W2951932242 on OpenAlexafffund
Dan Zhang, Lin Wang

Bibliographic record

VenueChaos An Interdisciplinary Journal of Nonlinear Science · 2019
Typearticle
Languageen
FieldMedicine
TopicMathematical and Theoretical Epidemiology and Ecology Models
Canadian institutionsUniversity of New Brunswick
FundersCanadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMultistabilityChemostatKineticsMonotone polygonLimitingChaoticBiological systemOrder (exchange)MathematicsControl theory (sociology)Statistical physicsNonlinear systemBiologyPhysicsComputer scienceEconomicsClassical mechanics

Abstract

fetched live from OpenAlex

In this paper, we consider a discrete size-structured nonlinear chemostat model with inhibitory kinetics and multiple competing species. We show that, same as in models with monotone increasing nutrient uptake response functionals studied in the literature, one essential growth-limiting nutrient can support at most one species. More interestingly, we show that, differing from monotone increasing kinetics, inhibitory kinetics can induce several types of multistability and the competitive outcome is initial condition dependent. The species with the smallest lower break-even value is not always the winning species, and the winning species can exhibit sustained periodic oscillations and even chaotic irregular oscillations.

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 score0.947
Threshold uncertainty score0.541

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.014
GPT teacher head0.331
Teacher spread0.317 · 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

Citations3
Published2019
Admission routes2
Has abstractyes

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