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Record W2111080754 · doi:10.1142/s0217979203022453

Global Instability, Limiting-State Selection and Nonlinear Pattern Formation

2003· article· en· W2111080754 on OpenAlexaff
Jianjun Xu, Huang Yong-nian

Bibliographic record

VenueInternational Journal of Modern Physics B · 2003
Typearticle
Languageen
FieldMaterials Science
TopicSolidification and crystal growth phenomena
Canadian institutionsMcGill University
Fundersnot available
KeywordsNonlinear systemInstabilityLimitingStatistical physicsQuantization (signal processing)ScalingBoundary value problemEigenvalues and eigenvectorsPhase transitionTheoretical physicsPhysicsComputer scienceMathematicsMechanicsCondensed matter physicsQuantum mechanicsMechanical engineeringGeometry

Abstract

fetched live from OpenAlex

Interfacial pattern formation in phase transition and crystal growth and material science is one of the most important subjects in the broad field of nonlinear science. This subject involves the concepts and issues, include the basic states, global stability, limiting-state selection, quantization conditions of eigenvalues, scaling law and free boundary problems of dynamic system far away from the equilibrium state. This talk attempts to explore these issues through the two prototype problems: (1). dendritic growth from melt; (2). disc-like crystal growth from melt. These problems are highly challenging fundamental problems in condensed matter physics and material science, which have preoccupied many investigators from various areas of science, including applied mathematics for a long period of time. We shall summarize the major results achieved in terms of a unified systematic asymptotic approach during the last decade. For the case of dendritic growth, these results described the wave-characteristics of interface evolution and led to the so-called interfacial wave (IFW) theory.

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: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

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 integrity0.0000.000
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 head0.021
GPT teacher head0.272
Teacher spread0.251 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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