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Record W3163799670

Correlation of Mechanical and Hydration Properties of Soft Phytoglycogen Nanoparticles

2019· article· en· W3163799670 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAPS March Meeting Abstracts · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsNanoparticleMaterials scienceParticle (ecology)ChemistryChemical engineeringNanotechnology
DOInot available

Abstract

fetched live from OpenAlex

Abstract Phytoglycogen nanoparticles are highly branched polymers of anhydroglucose units (AGUs) produced as soft, compact nanoparticles by sweet corn. By combining results of dialysis, ellipsometry and gravimetric analysis experiments, we constructed a master plot of the osmotic pressure Π -concentration C data for phytoglycogen nanoparticles that spans the complete range ∼ 0% w/w C ∼ 100 % w/w. The distinctive shape of the Π C curve for phytoglycogen differs significantly from that of dextran, a lightly branched polysaccharide also made up of AGUs but not in the form of particles, especially near concentrations corresponding to contact between the nanoparticles. By calculating the dependence of the osmotic pressure on the volume per particle, we determined the increase in the bulk modulus of the particles with decreasing particle volume due to removal of water from the particles upon compression. This approach allowed us to quantify the strong correlation between the mechanical and hydration properties of phytoglycogen nanoparticles.

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.

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)0.001
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 score0.054
Threshold uncertainty score0.115

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.030
GPT teacher head0.221
Teacher spread0.192 · 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