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Record W3172211755 · doi:10.1016/j.ahr.2021.100017

No-added-oil mediterranean diet: A novel aging deceleration diet?

2021· article· en· W3172211755 on OpenAlexaff
Mohammed Abrahim

Bibliographic record

VenueAging and Health Research · 2021
Typearticle
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMediterranean dietCalorieLongevityMediterranean climateNutrientOlive oilFood scienceLife expectancyMealFortificationBiologyDietary fiberMedicineEnvironmental healthGerontologyEcologyEndocrinologyInternal medicine

Abstract

fetched live from OpenAlex

The Mediterranean diet has been associated with reduced morbidity and mortality as well as increased longevity. This dietary pattern relies heavily on fresh vegetables and fruits, whole grains, nuts, and occasionally fish and olive oil. Olive oil, despite being calorie-dense and nutrient-poor, was hailed as the hallmark of the healthy Mediterranean diet. Yet, caloric restriction and a low-fat diet are also associated with reducing aging-related chronic diseases and increasing life expectancy. Accordingly, the author proposes a novel variant of the Mediterranean diet termed no-added-oil Mediterranean diet and hypothesizes that such a novel diet could potentially slow down the aging process via reducing the bioaccessibility and density of the calories without significantly jeopardizing meal volume, fiber, or antioxidant content. Further research is needed to test this proposed novel dietary approach.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.339
GPT teacher head0.488
Teacher spread0.149 · 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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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