MétaCan
Menu
Back to cohort
Record W2337449815 · doi:10.1094/cchem-08-15-0175-r

Characterization of Maize Starch Nanoparticles Prepared by Acid Hydrolysis

2015· article· en· W2337449815 on OpenAlexaff
Mariana Perez Herrera, Thava Vasanthan, R. Hoover

Bibliographic record

VenueCereal Chemistry · 2015
Typearticle
Languageen
FieldNursing
TopicFood composition and properties
Canadian institutionsMemorial University of NewfoundlandUniversity of Alberta
Fundersnot available
KeywordsChemistryCrystallinityAmyloseStarchHydrolysisMaize starchAcid hydrolysisFood scienceBiochemistryCrystallography

Abstract

fetched live from OpenAlex

Starch nanoparticles (SNP) from maize starches of varying amylose content (0–71%) were prepared by acid hydrolysis (3.16M H 2 SO 4, at 40°C up to 6 days) followed by repeated water washings. During the washing cycles, nonwaxy starches (normal, Hylon V, and Hylon VII) had suspended particles in the water washings, which were not evident in waxy starch. Microscopic examination revealed the presence of SNP in the “cloudy supernatants” of nonwaxy starches and in the “final washed residue” of waxy maize. The objective of this study was to collect SNP fractions accordingly and determine whether variation in the native starch amylose content would influence the yield, morphology, and crystallinity of the SNP. In nonwaxy starches, the yield of SNP increased up to 26.6% with hydrolysis time and was proportional to the amylose content. Morphology of SNP differed with starch type: flat/elliptical (500 nm) in waxy, oval/irregular (50–200 nm) in normal, oval/round (40–50 nm) in Hylon V, and square/polygonal (50–100 nm) in Hylon VII. X‐ray diffraction confirmed the presence of A‐type crystals in SNP from all starch types and a crystalline transformation from B‐ to A‐type in Hylon starches. The relative crystallinity of SNP was higher than their native starch counterparts.

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 score0.005
Threshold uncertainty score0.344

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 head0.019
GPT teacher head0.236
Teacher spread0.217 · 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

Citations45
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueCereal ChemistrySame topicFood composition and propertiesFrench-language works237,207