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Record W3200943405 · doi:10.1136/bmjsem-2021-001082

Portuguese Football Federation consensus statement 2020: nutrition and performance in football

2021· article· en· W3200943405 on OpenAlexaff
Rodrigo Abreu, Pedro Figueiredo, Paulo Beckert, José Pedro Marques, Samuel Amorim, Carlos Alberto Caetano, Pedro Carvalho, Carla Sá, Ricardo Cotovio, Joana Cruz, Tiago Dias, Gonçalo Fernandes, Elton Gonçalves, César Leão, Alexandre Leitão, João Lopes, Eduardo Machado, Monica Araujo das Neves, André Luiz de Oliveira, Ana Isabel Pereira, Bruno Pereira, Fernando Ribeiro, Luis M Silva, Filipe Antônio de Barros Sousa, Tânia Tinoco, Vítor Hugo Teixeira, Mónica Sousa, João Brito

Bibliographic record

VenueBMJ Open Sport & Exercise Medicine · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle metabolism and nutrition
Canadian institutionsInstitute of Nutrition, Metabolism and Diabetes
Fundersnot available
KeywordsFootballPortugueseAthletesEliteScientific evidenceElite athletesRehabilitationPsychologyApplied psychologyPublic relationsMedical educationPolitical scienceMedicinePhysical therapyLaw

Abstract

fetched live from OpenAlex

Nutrition is an undeniable part of promoting health and performance among football (soccer) players. Nevertheless, nutritional strategies adopted in elite football can vary significantly depending on culture, habit and practical constraints and might not always be supported by scientific evidence. Therefore, a group of 28 Portuguese experts on sports nutrition, sports science and sports medicine sought to discuss current practices in the elite football landscape and review the existing evidence on nutritional strategies to be applied when supporting football players. Starting from understanding football's physical and physiological demands, five different moments were identified: preparing to play, match-day, recovery after matches, between matches and during injury or rehabilitation periods. When applicable, specificities of nutritional support to young athletes and female players were also addressed. The result is a set of practical recommendations that gathered consensus among involved experts, highlighting carbohydrates periodisation, hydration and conscious use of dietary supplements.

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)0.001
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 score0.490
Threshold uncertainty score0.702

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0000.000
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 head0.025
GPT teacher head0.323
Teacher spread0.298 · 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.

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

Citations34
Published2021
Admission routes1
Has abstractyes

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