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Record W2035719542 · doi:10.1021/jp908814t

Ion Solvation in a Water−Urea Mixture

2009· article· en· W2035719542 on OpenAlexaff
Takeshi Yamazaki, Andriy Kovalenko, Vladimir Murashov, G. N. Patey

Bibliographic record

VenueThe Journal of Physical Chemistry B · 2009
Typearticle
Languageen
FieldChemistry
TopicMass Spectrometry Techniques and Applications
Canadian institutionsNational Institute for NanotechnologyUniversity of British Columbia
Fundersnot available
KeywordsSolvationUreaIonChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

We employ molecular dynamics simulations and the reference interaction site model (RISM) integral equation theory to study the solvation structure and solvation thermodynamics of the transfer process from water to a water-urea mixture. Simple positive and negative ions together with uncharged species of the same size are used as crude models for the hydrophilic and hydrophobic groups of a protein. We find that urea preferentially solvates positively charged species. The solvation free energies obtained indicate that larger solutes favor the transfer from water to a water-urea mixture. The decomposition of the transfer free energy into the energetic and entropic terms shows that the energetic part is much larger than the entropic one and tends to dominate the transfer process, supporting the direct mechanism of urea-denaturation. In addition, the effect of urea on the water liquid structure is discussed from the viewpoint of solvation entropy.

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 score0.019
Threshold uncertainty score0.446

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 head0.007
GPT teacher head0.249
Teacher spread0.242 · 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

Citations34
Published2009
Admission routes1
Has abstractyes

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