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Record W2770896795 · doi:10.1503/cmaj.733381

The importance of study design in the assessment of nonnutritive sweeteners and cardiometabolic health

2017· letter· en· W2770896795 on OpenAlexaffvenue
John L. Sievenpiper, Tauseef Khan, Vanessa Ha, Effie Viguiliouk, Rodney Auyeung

Bibliographic record

VenueCanadian Medical Association Journal · 2017
Typeletter
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsHamilton Health SciencesMcMaster UniversityUniversity of TorontoSt. Michael's Hospital
Fundersnot available
KeywordsRandomized controlled trialMedicineArtificial SweetenerAlternative medicineComputer scienceEnvironmental healthFood scienceSurgeryPathologyChemistry

Abstract

fetched live from OpenAlex

Although we applaud Azad and colleagues for a comprehensive review of nonnutritive sweeteners (NNS) and cardiometabolic health,[1][1] we are concerned that important methodological considerations were overlooked. In interpreting the pooled analyses of randomized controlled trials (RCTs), the

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.655
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.021
GPT teacher head0.319
Teacher spread0.297 · 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 designNot applicable
Domainnot available
GenreCommentary

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

Citations38
Published2017
Admission routes2
Has abstractyes

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