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Record W2049641358 · doi:10.3109/02652048.2014.913723

Preparation of a novel rape pollen shell microencapsulation and its use for protein adsorption and pH-controlled release

2014· article· en· W2049641358 on OpenAlexaff
Hongbo Ma, Peiqi Zhang, Jidong Wang, Xu XianJu, Hui Zhang, Zhenhua Zhang, Yongchun Zhang, Yunwang Ning

Bibliographic record

VenueJournal of Microencapsulation · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicProteins in Food Systems
Canadian institutionsDepartment of Environment and Conservation
Fundersnot available
KeywordsAdsorptionScanning electron microscopeChemical engineeringHydrothermal carbonizationHydrothermal circulationMaterials sciencePollenBovine serum albuminCarbonizationChromatographyControlled releaseNuclear chemistryChemistryNanotechnologyOrganic chemistryBotanyComposite material

Abstract

fetched live from OpenAlex

This study aims to synthesize hollow microspheres (HMS) from rape pollen via H3PO4 hydrothermal carbonization. The rape pollen hollow shell was used as the carrier and bovine serum albumin as a model protein. The properties of HMS were characterized by scanning electron microscope (SEM), solid-state nuclear magnetic resonance and elemental analysis. The SEM images clearly showed that the HMS had perfect spherical morphology and porous hollow surface. In the separated filtrate, a large number of sucroses were detected by high-performance liquid chromatography, suggesting that the hydrolysis of starch molecules occurred during the hydrothermal process. The formation of HMS was that the rape pollen inclusion was removed from rape pollen shell to preserve integral HMS by H3PO4 hydrothermal. The HMS possessed amphiphilic surfaces, which was suitable for protein adsorpion and pH-controlled release application.

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 score0.001
Threshold uncertainty score0.001

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)0.0000.000

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 head0.256
Teacher spread0.226 · 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

Citations18
Published2014
Admission routes1
Has abstractyes

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