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Record W1980523124 · doi:10.1081/fbt-200063458

Citric Acid Production by<i>Aspergillus niger</i>Using Date-Based Medium Fortified with Whey and Additives

2005· article· en· W1980523124 on OpenAlex

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

VenueFood Biotechnology · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPolysaccharides and Plant Cell Walls
Canadian institutionsUniversity of Manitoba
FundersCooperative State Research, Education, and Extension ServiceNorth Carolina Agricultural and Technical State UniversityNorth Carolina State UniversityU.S. Department of Agriculture
KeywordsCitric acidAspergillus nigerFood scienceChemistryMethanolFermentationPhosphateBiochemistryOrganic chemistry

Abstract

fetched live from OpenAlex

The ability of Aspergillus niger to produce citric acid from dates was evaluated. Two strains of A. niger (ATCC 6275 and 9642) were grown in media containing different concentrations of date extract or molasses fortified with whey, methanol and tricalcium phosphate. The fermentation experiments were conducted at 25° C for 12 days and samples were withdrawn at different time intervals and analyzed for their citric acid content. Results showed that a high level of citric acid (32.4gL−1) was produced by A. niger ATCC 6275 in 20% molasses in whey. When methanol and tricalcium phosphate were added, a significant increase in citric acid production was recorded (P < 0.05). Citric acid concentrations were 38.4 and 42.4 gL−1, in media fortified with methanol and tricalcium phosphate, respectively. Our results showed that molasses could be used as a carbohydrate source for the production of citric acid. Strain type, addition of whey, methanol and tricalcium phosphate had a significant impact on citric acid production by A. niger.

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 score0.043
Threshold uncertainty score0.279

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 head0.014
GPT teacher head0.184
Teacher spread0.171 · 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