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Record W4412199776 · doi:10.54117/ijnfs.v4i2.84

Production and Characterization of Fruit Bars Produced from the Mucilaginous Pulp of Garcinia kola

2025· article· en· W4412199776 on OpenAlexaff
Nuria Chinonyerem Oganezi, Uchenna Okonkwo

Bibliographic record

VenueIPS Journal of Nutrition and Food Science · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant Physiology and Cultivation Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsGarcinia kolaPulp (tooth)HorticultureGarciniaBotanyChemistryBiologyDentistryMedicine

Abstract

fetched live from OpenAlex

Fruit bars were produced from exotic Garcinia kola fruit pulp puree at different concentrations. The bars were sweetened using 'date fruit paste', aspartame and sucrose. Hydrocolloids such as guar gum, xanthan gum and gelatin were added for stabilization. Analysis of the sensory results showed that the aspartame sweetened bars were preferred for their crispiness, taste color and mouthfeel. Further characterization of the bar samples with overall acceptability score ≥ 5.0 indicated that while fruit bars sweetened with aspartame and stabilized using gelatin was higher in crude protein content, the sucrose sweetened bars had higher carbohydrate content. The energy values of the bars ranged between 265.59 and 348.15 kcal/100g. Essential minerals were present in appreciable amounts in the fruit bars samples in this order: potassium>calcium>phosphorus>sodium>magnesium>iron>zinc. The results also showed that the G. kola fruit bars were low in antinutrients and contains beneficial antioxidants and bioactive compounds such as vitamin E, flavonoids, carotenoids, tannins, alkaloids and phenols. The pH of the bars (3.0 – 4.0) and the acidity values (0.16 – 0.22%) is an indication of potential shelf stability of the bars.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.140

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 head0.026
GPT teacher head0.230
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

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

Citations0
Published2025
Admission routes1
Has abstractyes

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