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Record W2082118539 · doi:10.1088/0305-4470/39/45/003

Self-avoiding walks in a slab: rigorous results

2006· article· en· W2082118539 on OpenAlexafffund
E J Janse van Rensburg, Enzo Orlandini, S G Whittingon

Bibliographic record

VenueJournal of Physics A Mathematical and General · 2006
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of TorontoYork University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLimitingSlabBounding overwatchEntropic forcePhase diagramPhysicsStatistical physicsPlane (geometry)Phase transitionLattice (music)Limit (mathematics)MathematicsClassical mechanicsCondensed matter physicsPhase (matter)Mathematical analysisQuantum mechanicsGeometryComputer science

Abstract

fetched live from OpenAlex

A polymer in the confined spaces between colloid particles loses entropy and exerts a repulsive entropic force on the confining particles. This situation can be modelled by a self-avoiding walk confined in a slab between two parallel planes in the lattice. In this paper, we prove the existence of a limiting free energy for the general case that the walk is interacting with the parallel bounding planes. We also prove that the limiting free energy is strictly increasing with the distance between the bounding planes in some regions of the phase diagram. These results demonstrate the presence of a non-zero repulsive entropic force in the model. Finally, we also examine the relation between the limiting free energy in this model and the limiting free energy in a model of walks adsorbing onto a single plane. We prove that these limiting free energies are equal in some regions of the phase diagram in the limit that the width of the slab between the parallel bounding planes is taken to infinity.

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)0.002
metaresearch head score (Gemma)0.007
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: none
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.001
Science and technology studies0.0010.003
Scholarly communication0.0020.004
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.217
Teacher spread0.208 · 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

Citations49
Published2006
Admission routes2
Has abstractyes

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Same venueJournal of Physics A Mathematical and GeneralSame topicMaterial Dynamics and PropertiesFrench-language works237,207