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Aspartame Consumption and Cancer Risk: A Systematic Review and Meta-Analysis Protocol

2024· review· en· W4404887918 on OpenAlexaboutno aff
Saman Rahimi Tanyani, Aram Halimi, Yaser Soleimani, Alireza Mosavi Jarrahi

Bibliographic record

VenueAsian Pacific Journal of Environment and Cancer · 2024
Typereview
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsnot available
Fundersnot available
KeywordsMeta-analysisProtocol (science)AspartameMedicineInternal medicineAlternative medicineBiologyPathologyFood science

Abstract

fetched live from OpenAlex

Background: Aspartame, a widely used artificial sweetener, has been under scrutiny for its potential carcinogenic effects. Although early studies raised concerns about its link to cancer, particularly in animal models, more recent human studies have produced mixed results. This protocol aims to systematically review the association between aspartame consumption and cancer risk. Methods: A systematic review and meta-analysis will be conducted by searching databases including MEDLINE, Scopus, and Web of Science. Eligible studies will involve human participants exposed to aspartame and assess cancer incidence as the primary outcome. Data extraction will include study characteristics, exposure levels, and cancer outcomes. Risk of bias will be assessed using the Newcastle-Ottawa Scale, and data will be synthesized through qualitative and quantitative methods, including meta-analysis where applicable. Results: This review will present pooled risk estimates for cancer associated with aspartame consumption and explore variations by cancer type, dose, and duration of exposure. Conclusion: This study will provide an updated synthesis of evidence regarding aspartame consumption and its potential role in cancer development, informing future public health guidelines.

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: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.799
Threshold uncertainty score0.821

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0050.001
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)0.0010.000

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 head0.072
GPT teacher head0.370
Teacher spread0.299 · 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 designSystematic review
Domainnot available
GenreReview

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
Published2024
Admission routes1
Has abstractyes

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