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Record W2151429361 · doi:10.5539/jfr.v3n6p156

Determination of Aspartame Levels in Soft Drinks Consumed in Ankara, Turkey

2014· article· en· W2151429361 on OpenAlexvenueno aff
Elif ÇELİK, Buket Er Demirhan, Burak Demirhan, Gülderen Yentür

Bibliographic record

VenueJournal of Food Research · 2014
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsAspartameFood scienceChemistrySoft drinkArtificial SweetenerSugar

Abstract

fetched live from OpenAlex

<p>Aspartame is commonly used as artificial sweeteners in several food products. Excess amounts of aspartame can be harmful to human health. Therefore, the investigation of aspartame levels in foods is important. The aim of this study was to determine levels of aspartame<strong> </strong>in soft drinks and to evaluate whether these amounts were within the Turkish Food Codex values or not. For this purpose, total number of 90 soft drink samples (A, B, C, D, E and F brands) including 15 from each brand were collected from supermarkets in Ankara province, Turkey . In this study, spectrophotometric method was used for the quantitative determination of aspartame in the samples. Mean levels (± S.E) of aspartame<sub> </sub>in samples of A, B, C, D, E and F brand were found as 156.81±7.29 mg/L, 208.67±8.97 mg/L, 236.58±17.91 mg/L, 299.54±26.19 mg/L, 202.39±8.08 mg/L and 223.28±14.08 mg/L, respectively. Our data revealed that mean levels of aspartame were found within Turkish Food Codex in all samples. However, some samples were not found appropriate according to the label information.</p>

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)0.003
metaresearch head score (Gemma)0.001
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 score0.133
Threshold uncertainty score0.323

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
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 head0.098
GPT teacher head0.393
Teacher spread0.295 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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