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Record W1989259957 · doi:10.1021/ci020269x

Path-Space Ratio as a Molecular Shape Descriptor of Polymer Conformation

2002· article· en· W1989259957 on OpenAlexafffund
Tomas Edvinsson, Gustavo A. Arteca, Christer Elvingson

Bibliographic record

VenueJournal of Chemical Information and Computer Sciences · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicForce Microscopy Techniques and Applications
Canadian institutionsLaurentian University
FundersNatural Sciences and Engineering Research Council of CanadaUppsala Universitet
KeywordsDimensionless quantityWritheQuantum entanglementChain (unit)Topology (electrical circuits)PolymerKnot (papermaking)Measure (data warehouse)Path (computing)Path lengthConfiguration spaceSpace (punctuation)MathematicsWork (physics)Statistical physicsComputer sciencePhysicsMaterials scienceGeometryCombinatoricsData miningTwistThermodynamicsQuantum mechanics

Abstract

fetched live from OpenAlex

Polymers at interfaces exhibit properties that cannot be completely captured by descriptors of mean molecular size. Recent work in the literature shows that a combined analysis of mean size and chain entanglement provides a more discriminating approach to understanding the onset of configurational transitions in these systems. Usually, chain entanglement is characterized by properties such as the mean overcrossing number or the chain's writhe; these are powerful properties but their evaluation can be computationally demanding. In this work, we introduce a geometrical descriptor of polymer shape, termed the path-space ratio zeta, aimed at quantifying essential features of chain complexity, but at a lower computational cost. The descriptor includes information on chain geometry and topology. The path-space ratio zeta is built by taking into account two key ideas: (a) a dimensionless measure of length along the backbone of the polymer, and (b) the behavior of topological "knot energies". Here, we compare zeta with other approaches to quantify polymer geometry and connectivity. Particular attention is devoted to the ability of these descriptors to discriminate and quantify conformational changes in grafted polymers under compression. We show that, for these types of applications, the path-space ratio presents a fast alternative to the mean overcrossing number.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.009
GPT teacher head0.239
Teacher spread0.230 · 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 designBench or experimental
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
Published2002
Admission routes2
Has abstractyes

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