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Record W4376256256 · doi:10.1002/ep.14172

Molecular characterization of a new strain of <i>Aspergillus</i> and ricinoleic acid production from castor oil by the fungus

2023· article· en· W4376256256 on OpenAlexaff
Shikha Singh, Sumit Sharma, Saurabh Jyoti Sarma, Satinder Kaur Brar

Bibliographic record

VenueEnvironmental Progress & Sustainable Energy · 2023
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolic Engineering and Bioproduction
Canadian institutionsYork University
Fundersnot available
KeywordsRicinoleic acidCastor oilMetaboliteChemistryAspergillus flavusStrain (injury)Yield (engineering)Organic chemistryFood scienceChromatographyCosmeticsBiochemistryBiologyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

Abstract The derivatives of castor oil have wide industrial applications. Different strains were isolated that metabolize the castor oil. Among these, Isolate D which was later identified as Aspergillus flavus BU22S was selected for further study. Major metabolite produced by the strain was extracted and identified using mass spectrometry (MS) followed by HPLC analysis. The metabolite was found to be ricinoleic acid. Ricinoleic acid is widely used in polymer industries, cosmetics, pharmaceutical industries, lubricants, and in textiles. The product yield of the selected isolate was studied with different castor oil concentrations under different process conditions. Agitation speed as well as oil concentration were found to have a significant effect on ricinoleic acid production. The best yield, that is, 79.5 g/kg of total oil was obtained at a lower agitation speed. The strain consumed some amount of oil, which can be reduced from 90% to 29% by optimizing the process parameters.

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 score0.033
Threshold uncertainty score0.448

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 head0.002
GPT teacher head0.173
Teacher spread0.170 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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