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Record W2089484846 · doi:10.1002/cjce.21851

Non‐selective hydrolysis of tuna fish oil for producing free fatty acids containing docosahexaenoic acid

2013· article· en· W2089484846 on OpenAlexafffundvenue
Aditi Sharma, Satyendra P. Chaurasia, Ajay K. Dalai

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Catalysis and Immobilization
Canadian institutionsUniversity of Saskatchewan
FundersUniversity of Saskatchewan
KeywordsChemistryTunaHydrolysisCandida antarcticaLipaseFish oilFourier transform infrared spectroscopyNuclear chemistryMichaelis–Menten kineticsDocosahexaenoic acidSolventActivation energyFatty acidChromatographyEnzymeOrganic chemistryEnzyme assayFish <Actinopterygii>Polyunsaturated fatty acidBiologyFisheryChemical engineering

Abstract

fetched live from OpenAlex

Abstract The nature of immobilised Candida antarctica lipase‐B (CAL‐B) catalysed hydrolysis of tuna fish oil was studied with parameters such as solvent and water concentration, temperature, speed of agitation and enzyme loading. Immobilised CAL‐B and support material immobead‐150 were characterised with BET surface area, particle size analyser and Fourier transform infrared spectroscopy (FT‐IR) to record their physiochemical properties. The maximum rate of reaction ( V max ) of 500 µmol of free fatty acids (FFAs) per mL reaction mixture per h and Michaelis−Menten constant ( K M ) of 2115 µmol FFAs/mL were found for Michaelis−Menten type kinetic model. Activation energy (E) of 26.1 KJ/mol was calculated for immobilised CAL‐B. The 55.9% conversion of triglycerides was observed after the third use of the immobilised CAL‐B. The activity retention of immobilised CAL‐B reduced to 33.5% after the fourth repeated use of the enzyme.

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)0.001
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 score0.002
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.005
GPT teacher head0.187
Teacher spread0.182 · 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

Citations11
Published2013
Admission routes3
Has abstractyes

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