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Record W4414657016 · doi:10.3389/fnut.2025.1692429

Correction: Gender-specific insights into adherence to Mediterranean diet and lifestyle: analysis of 4,000 responses from the MEDIET4ALL project

2025· erratum· en· W4414657016 on OpenAlexaff
Mohamed Ali Boujelbane, Achraf Ammar, Atef Salem, Mohamed Kerkeni, Khaled Trabelsi, Bassem Bouaziz, Liwa Masmoudi, Juliane Heydenreich, Christiana Schallhorn, Gabriel Müller, Hadeel Ghazzawi, Adam Tawfiq Amawi, Bekir Erhan Orhan, Giuseppe Grosso, Osama Abdelkarim, Tarak Driss, Kaïs El Abed, Piotr Żmijewski, Nasreddine Benbettaïeb, Clément Poulain, Laura Reyes-Uribe, Amparo Gamero, Marta Cuenca-Ortolá, Nicola Francesca, Concetta María Messina, Bent Lorenzen, Stefania Filice, Aadil Bajoub, El-Mehdi Ajal, El Amine Ajal, Majdouline Obtel, Sadjia Lahiani, Taha Khaldi, Nafaa Souissi, Omar Boukhris, Haitham Jahrami, Waqar Husain, Walid Mahdi, Hamdi Chtourou, Wolfgang I. Schöllhorn

Bibliographic record

VenueFrontiers in Nutrition · 2025
Typeerratum
Languageen
FieldMedicine
TopicNutritional Studies and Diet
Canadian institutionsInnovation Cluster (Canada)
Fundersnot available
KeywordsMediterranean dietMediterranean climateConsumption (sociology)Feeding behavior

Abstract

fetched live from OpenAlex

There was a mistake in figure 1 as published. Figure 1 illustrates the geographical distribution and sample sizes of study participants from selected Mediterranean and non-Mediterranean countries. However, the figure mistakenly contained an incorrect representation of the Moroccan border. The corrected figure 1 appears below.

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)0.015
metaresearch head score (Gemma)0.263
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.117
Threshold uncertainty score0.390

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0150.263
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0020.002
Bibliometrics0.0050.006
Science and technology studies0.0040.003
Scholarly communication0.0040.003
Open science0.0040.003
Research integrity0.0050.009
Insufficient payload (model declined to judge)0.1170.054

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 head0.034
GPT teacher head0.299
Teacher spread0.265 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations5
Published2025
Admission routes1
Has abstractyes

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