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Record W3040002326 · doi:10.14740/jocmr4258

A Study of Artificial Sweeteners and Thyroid Cancer Risk

2020· article· en· W3040002326 on OpenAlexvenueno aff
Navdeep Singh, Sandeep Singh Lubana, Saurabh Arora, Issac Sachmechi

Bibliographic record

VenueJournal of Clinical Medicine Research · 2020
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsnot available
FundersKozuki Foundation
KeywordsMedicineArtificial SweetenerObservational studyThyroid cancerThyroidInternal medicineRetrospective cohort studySurgeryFood science

Abstract

fetched live from OpenAlex

BACKGROUND: In recent decades, data from certain observational studies have stirred controversy over artificial sweeteners by linking them with certain malignancies. As the incidences of artificial sweetener consumption and thyroid cancer are both increasing, our study aimed to determine any possible association between them. METHODS: This retrospective observational study enrolled 50 patients (group 1) with proven diagnosis of well-differentiated thyroid cancer (WDTC) and 50 control subjects (group 2) diagnosed as having benign thyroid nodule by fine-needle aspiration. The survey questionnaire included the total amount and duration of intake of artificial sweeteners. RESULTS: Increased consumption of artificial sweeteners was noted in group 1 as compared to group 2, which was statistically significant (76% vs. 24%, P < 0.01). This study suggested that the use of an average of four packets (4 g) per day of artificial sweetener for an average duration of 5 years is associated with WDTC. CONCLUSIONS: Our study emphasizes the significance of artificial sweetener consumption as a potential risk factor for WDTC and increase in public awareness regarding this association if other studies in future report similar findings.

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)0.007
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.556
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.378
GPT teacher head0.572
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.

Study designOther design
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

Citations11
Published2020
Admission routes1
Has abstractyes

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