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Record W2957164155 · doi:10.21608/iccee.2018.34666

A Statistical Study on the Parameters Influences the Formation of Starch Nanoparticles through Acid Hydrolysis

2018· article· en· W2957164155 on OpenAlex
Fereshteh Bakhtiari, S.S.E.H. Elnashaie, Firoozeh Danafar, Fahimeh Kamali

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

VenueThe International Conference on Chemical and Environmental Engineering · 2018
Typearticle
Languageen
FieldChemistry
TopicAdsorption, diffusion, and thermodynamic properties of materials
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsHydrolysisStarchNanoparticleAcid hydrolysisChemistryChemical engineeringChromatographyFood scienceBiochemistryEngineering

Abstract

fetched live from OpenAlex

Starch is a natural, renewable and biodegradable polymer produced by many plants as a source of stored energy. It is the second most abundant biomass material in nature. Starch has a concentric semicrystalline multiscale structure. This structure allows the production of new nano elements through disruption of amorphous domain by acid hydrolysis. Current environmental concerns have turned starch nanoparticles into candidates of growing interest as bio-nanofiller for nanocomposite applications. In this study, the effects of different parameters, while the time of reaction was limited to 1 hr, on starch nano particles formation was investigated. A response surface methodology analysis has been undertaken. The average size of starch nanoparticle obtained in this study was 37.76 nm.

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)0.000
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 score0.034
Threshold uncertainty score0.445

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 head0.027
GPT teacher head0.231
Teacher spread0.204 · 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