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Record W2016500905 · doi:10.1063/1.1386420

Statistical mechanics of solvophobic aggregation: Additive and cooperative effects

2001· article· en· W2016500905 on OpenAlexafffund
Seishi Shimizu, Hue Sun Chan

Bibliographic record

VenueThe Journal of Chemical Physics · 2001
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Dynamics and Properties
Canadian institutionsUniversity of Toronto
FundersMedical Research Council CanadaCanada Research Chairs
KeywordsSolvophobicCooperativityPairwise comparisonChemistryStatistical physicsChemical physicsThermodynamicsPhysicsMathematicsMoleculeStatistics

Abstract

fetched live from OpenAlex

Effects of possible non-pairwise-additive interactions on solvophobic aggregation are analyzed. A simple lattice model of binary solution with attractive solute-solute interactions is introduced to delineate the role of multiple-body effects in solute clustering and aggregation. Additive (noncooperative), cooperative, and anti-cooperative intersolute interactions are modeled by multiple-solute potentials that are respectively equal to, more favorable than, and less favorable than the sum of pairwise solute interactions. Under appropriate conditions, pairwise additive interactions and even interactions with significant anti-cooperativity can lead to aggregation and demixing. Cooperative interactions are not necessary for solute aggregation. Similarities and differences between solute aggregation and hydrophobic collapse of proteinlike heteropolymers are investigated. On average, heteropolymer collapse transitions as a function of solvophobic composition are significantly less sharp than the corresponding solute aggregation transitions. This difference is seen as a direct consequence of chain connectivity constraints.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.184

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 communication0.0000.000
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 head0.227
Teacher spread0.218 · 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

Citations19
Published2001
Admission routes2
Has abstractyes

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