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Record W2618620859 · doi:10.1111/sapm.12181

Resonances in Bounded Media

2017· article· en· W2618620859 on OpenAlexafffund
David E. Amundsen

Bibliographic record

VenueStudies in Applied Mathematics · 2017
Typearticle
Languageen
FieldMathematics
TopicDifferential Equations and Numerical Methods
Canadian institutionsCarleton University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDissipative systemNonlinear systemBounded functionAmplitudeMathematicsMathematical analysisSpectrum (functional analysis)PhysicsForcing (mathematics)Truncation (statistics)ObservableQuantum mechanics

Abstract

fetched live from OpenAlex

Resonant behavior in bounded domains and under the influence of weakly periodic forcing with magnitude is studied for a general class of one‐dimensional nonlinear wave systems. The model encompasses and provides analogy to numerous physically motivated cases such as acoustic resonators. Through a generalized weakly nonlinear analysis the linear response and associated resonant spectrum may be determined. In the case where the spectrum is sufficiently noncommensurate a single mode response emerges with amplitude . Dependence upon detuning and dissipative effects follow immediately from the subsequent nonlinear balance. In the case where the spectrum is commensurate a multimodal response arises, leading to a coupled system of solvability conditions. The amplitude of the response depends in detail on the commensurate structure, in the case where it is fully commensurate. This is in keeping with the well‐known dichotomy between responses for acoustic waves in open and closed tubes. Through continuous variation of the model system, the nature of the transition between these distinct regimes is then studied and through an appropriate modal truncation the connection is achieved. A numerical example is presented to further illustrate and corroborate the general analysis.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.334
GPT teacher head0.486
Teacher spread0.152 · 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 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

Citations5
Published2017
Admission routes2
Has abstractyes

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