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Record W4309913131 · doi:10.54097/hset.v19i.2837

The Influence of Low-Carbohydrate and Low-Fat Diet on Cardiovascular Disease

2022· article· en· W4309913131 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueHighlights in Science Engineering and Technology · 2022
Typearticle
Languageen
FieldMedicine
TopicDiet and metabolism studies
Canadian institutionsMcMaster University
Fundersnot available
KeywordsObesityOverweightSaturated fatMedicineStroke (engine)Blood pressureFood scienceDiseaseLow fat dietEndocrinologyCholesterolInternal medicineEnvironmental healthBiology

Abstract

fetched live from OpenAlex

It has become a consensus that low fat diet is the key to lose weight and keep slim. This study is important for obese and overweight individuals, who are at increased risk of CVD. The reduction of total fat in food is directly related to the reduction of individual cholesterol level and blood pressure, which also reveals the beneficial role of low-fat diet in preventing the risk of heart problems. Low-carb diets and low-fat diets can both help to lower the risk of CVD, but there’s no direct link between them. The basic mechanism is to improve other factors like hypertension and obesity which can be altered by healthy diets. Cutting back on saturated fatty acids can lower heart problems and stroke risk, because less cholesterol and saturated fats re consumed. Therefore, it is essential for us to eat correctly and healthily and take more exercise to prevent happening of CVD.

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.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score0.249

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.005
GPT teacher head0.204
Teacher spread0.199 · 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