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Record W1984102353 · doi:10.1139/v08-005

Partitioning of charged and neutral dextran-dye derivatives in biphasic cellulose nanocrystal suspensions

2008· article· en· W1984102353 on OpenAlexfundvenueno aff
Stephanie Beck-Candanedo, David Viet, Derek G. Gray

Bibliographic record

VenueCanadian Journal of Chemistry · 2008
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsnot available
FundersUniversité de MontréalNatural Sciences and Engineering Research Council of CanadaMcGill University
KeywordsChemistryPartition coefficientVirial coefficientDextranCelluloseAqueous solutionPolyelectrolytePartition (number theory)Polymer chemistryMoleculeMacromoleculeChromatographyOrganic chemistryComputational chemistryThermodynamicsPolymer

Abstract

fetched live from OpenAlex

The partitioning behaviour of dye-labeled dextrans of high molecular weight in aqueous suspensions of native cellulose nanocrystals was studied. Cellulose concentrations lie in the isotropic–nematic coexistence region. Blue dextrans of various molecular weights and degrees of substitution of dye molecules (anionic Cibacron blue 3G-A) were investigated. Increasing the total concentration of blue dextran and degree of dye substitution led to increasing partition coefficients. Increasing dextran molecular weight resulted in higher partition coefficients, in agreement with theory. Partition coefficients were larger than predicted theoretically using a second virial coefficient approximation. Electrostatic and entropic contributions to the partition coefficient of blue dextran are discussed. Dextrans labeled with neutral fluorescein isothiocyanate did not partition preferentially in this system.Key words: partition coefficient, cellulose nanocrystals, dextrans, degree of substitution, polyelectrolyte.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.024
GPT teacher head0.247
Teacher spread0.223 · 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 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
Published2008
Admission routes2
Has abstractyes

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Same venueCanadian Journal of ChemistrySame topicAdvanced Cellulose Research StudiesFrench-language works237,207