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Record W2329485694 · doi:10.1136/ebmed-2014-110138

Weight-loss diets only work when you follow them

2015· letter· en· W2329485694 on OpenAlexaff
Arya M. Sharma

Bibliographic record

VenueEvidence-Based Medicine · 2015
Typeletter
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsWeight lossOverweightLow calorie dietMedicineRandomized controlled trialCalorieObesityVery low calorie dietExcess weightInternal medicineAnimal scienceBiology

Abstract

fetched live from OpenAlex

Commentary on : Bazzano LA, Hu T, Reynolds K, et al. Effects of low-carbohydrate and low-fat diets: a randomized trial. Ann Intern Med 2014;161:309–18; and Johnston BC, Kanters S, Bandayrel K, et al. Comparison of weight loss among named diet programs in overweight and obese adults: a meta-analysis. JAMA 2014;312:923–33[OpenUrl][1]. Dietary interventions are the mainstay of behavioural obesity management, but exactly what type of diet may be most beneficial remains a matter of controversy.1 Thus, both academic and popular literature is flush with arguments in favour of specifically altering the macronutrient composition of diets for weight loss, be it to restrict calories from carbohydrates or fat intake or to increase protein intake. Commercial interest in these approaches ranging from multimillion corporations (eg, Weight Watchers, Atkins) to bestselling authors (eg, the Zone Diet); all promise easy and sustained weight loss. However is there really a big difference between the efficacy and effectiveness of these diets? This is the central question of the two studies. A prospective parallel group randomised trial was conducted by Bazzano and colleagues in 148 men and women without clinical cardiovascular disease and diabetes, comparing a … [1]: {openurl}?query=rft.jtitle%253DAnn%2BIntern%2BMed%26rft.volume%253D312%26rft.spage%253D309%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Commentary
About the Canadian research system: no · About a Canadian topic: no
Not applicablelow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Randomized triallow
models splitAgreement compares identical category sets and study designs across arms.

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)0.002
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.081
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.001

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 head0.106
GPT teacher head0.307
Teacher spread0.201 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designNot applicable · Randomized trial
Domainnot available
GenreCommentary · Empirical

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

Citations1
Published2015
Admission routes1
Has abstractyes

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