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Record W4415555909 · doi:10.54117/an7vv661

Use of Probiotics as Food Additives and its Legal Basis

2025· article· W4415555909 on OpenAlexaboutno aff
I. P. Nwakoby, I. H. Iheukwumere, C. M. Iheukwumere, N. E. Nwakoby, M. A. Idigo

Bibliographic record

VenueAfrican Journal of Nutrition and Applied Research · 2025
Typearticle
Language
FieldAgricultural and Biological Sciences
TopicFood Industry and Aquatic Biology
Canadian institutionsnot available
Fundersnot available
KeywordsQuality (philosophy)Food safetyHuman healthProbioticBottleneckProcess (computing)Action (physics)Health benefitsKey (lock)

Abstract

fetched live from OpenAlex

The global functional food market is expanding rapidly, with probiotics leading this growth due to consumer demand for health-promoting products. These live microorganisms are increasingly incorporated into diverse food matrices, from yogurts to cereals and meats. However, their use as food additives faces significant regulatory complexity. This review provides a comprehensive analysis of the scientific and legal frameworks governing probiotics as food additives. It first outlines the scientific basis for probiotics, including their mechanisms of action and the critical importance of strain-specificity and viability. The core of the paper presents a comparative analysis of regulatory approaches by major bodies like the U.S. FDA, the European EFSA, Health Canada, and Japan's MHLW. Key distinctions are made between pathways such as the GRAS notification in the U.S., the QPS approach in the EU, and novel food approvals. A central challenge is the approval of health claims, with the review contrasting EFSA's stringent evidence-based process with the U.S. structure/function system and Japan's FOSHU system. It also discusses challenges in quality control, labeling accuracy, and the lack of global harmonization. The conclusion emphasizes that fragmented legal frameworks act as a bottleneck for innovation. Future progress depends on generating robust clinical evidence and fostering international cooperation to harmonize safety and efficacy guidelines, ensuring consumer confidence and access to beneficial probiotic foods.

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 score0.358
Threshold uncertainty score0.378

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.135
GPT teacher head0.330
Teacher spread0.194 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

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