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Record W1984653348 · doi:10.5539/mas.v4n8p96

Determination of Process Stability and Response for Glucose Isomerisation Process

2010· article· en· W1984653348 on OpenAlexvenueno aff
Norliza Abd Rahman, M.A. Hussain

Bibliographic record

VenueModern Applied Science · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsnot available
FundersMinistério da Ciência, Tecnologia e InovaçãoKementerian Sains, Teknologi dan Inovasi
KeywordsFructoseVolumetric flow rateSteady state (chemistry)Eigenvalues and eigenvectorsIsomerizationChemistryProcess (computing)ChromatographyAnalytical Chemistry (journal)Materials scienceThermodynamicsBiochemistryPhysicsPhysical chemistryCatalysisComputer science

Abstract

fetched live from OpenAlex

Production of fructose from glucose isomerisation process using a commercial immobilized glucose isomerase (IGI), involved many factors such as pH, temperature, feed flow rate and initial glucose concentration. This study is focused on determination of process stability, eigenvalues,l, and response of the process, eigenvector,x, at various space velocity, D=F/V (F= feed flow rate mLmin-1 and V= volume of packed-bed reactor, 65mL) with initial steady state of glucose and fructose concentration in improving formation of fructose. Simplified Michelis-Menten model was derived for glucose isomerisation with initial concentrations of glucose from 18 gL-1. The temperature under study was 60ºC with pH of 7 and D from 0, 0.3,1, 5 and 10 per minute. From the results, the steady- state of glucose concentration was obtained at 16.375 g/L and 1.75 gL-1. At D = 0.3 the eigenvalues,l, for glucose and fructose are–0.3 and –0.0002 which show that the process is stable as the eigenvalues is negative whereas the faster response is given by the eigenvector,x with values of [-0.3;0]. Increase D will increase the response of the process but at same time maintain the stability of the process.

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)0.001
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 score0.064
Threshold uncertainty score0.217

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 head0.008
GPT teacher head0.260
Teacher spread0.252 · 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

Citations3
Published2010
Admission routes1
Has abstractyes

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