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Record W4323042708 · doi:10.1134/s1063784222110020

Сriteria for Adequacy of the Cascade of Feigenbaum Bifurcations and Cycles of the Sharkovsky Ordering in Models of Transformable Biophysical Processes

2022· article· en· W4323042708 on OpenAlexaboutno aff
A. Yu. Perevaryukha

Bibliographic record

VenueTechnical Physics · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAquatic and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsInterpretabilityCascadeStatistical physicsNonlinear systemBifurcationAction (physics)PopulationComputer scienceField (mathematics)Complex dynamicsLimit (mathematics)Applied mathematicsMathematicsPhysicsArtificial intelligenceMathematical analysisPure mathematicsChemistry

Abstract

fetched live from OpenAlex

Abstract The problem of development of a noncontradictory method for computer simulation for biophysical processes with clearly manifested staging and critical transformation is considered. Analogous models proposed earlier exhibit different behaviors with emergence of bifurcations, such as even and odd cycles, the coexistence of which is determined by the Sharkovsky theorem and in the limit of complication of cyclic behavior by trajectory chaotization. If, however, a model is interpreted in the field of biophysics, the coexistence of nonlinear effects becomes contradictory. In predicting the dynamics of biological resources with account for a regulating action, the iteration models generate undesirable nonlinear regimes of behavior (for example, in the case of the familiar Feigenbaum scenario). Complex effects connected with one another appear in cascades of emerging cycles with period p = 2i + 1, i → ∞, or in a cascade of cycles with p = 2i – 1, i → 0. The effects of an infinite bifurcation cascade and periodicity windows are determined by the fulfillment of the conditions of the Singer theorem. In this study, it is substantiated that bifurcations combined in one scenario cannot be explained in environmental reality and are not reflected in observed biophysical systems. Such mathematical artifacts turn out to be general for several biophysical models that differ drastically in their theoretical foundations. In this article, the insufficiently studied problem of essential interpretability (based on biological statistics) of the behavior of the class of computational models that are widely used in practical nature management. The chaotization in the real population dynamics has properties differing from those obtained in the cascade of period-doubling bifurcations. The formation of a nonattracting chaotic set in the form of a strange repeller better corresponds to actual chaos. It is shown that for describing transformation of processes in biological systems with external action (e.g., exploited population collapse), it is appropriate to use models with the emergence of alternative attractors. Such models better correspond to transitions between states of populations under exploitation than models with realization of bifurcation cycle cascades, strange Kantor attractors, and chaos regimes in the formulation of Lie and York in the form of a continuum of unstable trajectories of all periods. The hybrid models of living cycle with evolution stages that have been developed by the author earlier are in conformity with the proposed criteria for essential interpretation in ecology and in the prediction of biological systems. The correspondence analysis is based on scenarios of degradation of complexly structured population of red king crab and cod at shores of Kodiak Island (Alaska), stock crisis of salmon the Caspian Sea, and cod at the Canada shore, as well as bursts of population of insects, the models of which were described in the previous publications of the author.

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)0.003
metaresearch head score (Gemma)0.018
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.026
GPT teacher head0.219
Teacher spread0.193 · 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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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