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Record W4205618035 · doi:10.31590/ejosat.1045487

A SYSTEMATIC META-ANALYSIS OF AFLATOXIN B1 PRESENCE IN RED PEPPER

2022· article· en· W4205618035 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

VenueEuropean Journal of Science and Technology · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMycotoxins in Agriculture and Food
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsPepperAflatoxinSeasoningContext (archaeology)Meta-analysisToxicologyFood scienceBiotechnologyBiologyMedicineRaw material

Abstract

fetched live from OpenAlex

Aflatoxins are one of the pollutants that can be isolated from the dried food products, especially spices. Since red pepper is one of the most consumed spices all over the world, this research aimed to estimate the prevalence and concen-tration of aflatoxin B1 (AFB1) in different red pepper spices with the help of a systematic review and meta-analysis. Therefore, the articles published between January 2000 and December 6, 2020, were systematically collected from four well-known databases. In this context, 10 articles containing 455 samples in total among 981 articles were included in the meta-analysis according to the determined inclusion and exclusion criteria. According to the analysis results, the AFB1 prevalence of all studies was determined as 50.8%. The lowest and highest AFB1 concentrations were observed in seasoning paprika Korea (0.14 mg/kg) and Turkey (31.13 mg/kg), respectively. The result of this meta-analysis can be used in the evaluation and organization of solution actions to be devel-oped to reduce AFB1 exposure and prevent financial losses through the con-sumption of red pepper spice products.

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)0.004
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 score0.876
Threshold uncertainty score0.287

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.006
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.029
GPT teacher head0.222
Teacher spread0.192 · 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