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Record W2284370511 · doi:10.1139/apnm-2015-0514

Angiotensin-converting enzyme (<i>ACE-I/D</i>) polymorphism frequency in Brazilian soccer players

2016· article· en· W2284370511 on OpenAlexvenueno aff
Daniel Barbosa Coelho, Eduardo Mendonça Pimenta, Izinara Cruz Rosse, Christiano Eduardo Veneroso, Guilherme de Azambuja Pussieldi, Lenice Kapes Becker, Maria Raquel Santos Carvalho, Emerson Silami‐Garcia

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenetics and Physical Performance
Canadian institutionsnot available
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsGenotypeAngiotensin-converting enzymeAllele frequencyPolymorphism (computer science)AlleleGenotype frequencyGeneticsInternal medicineBiologyEndocrinologyMedicineGene

Abstract

fetched live from OpenAlex

This study aimed to analyze the angiotensin-converting enzyme (ACE-I/D) allelic and genotypic frequencies in Brazilian soccer players of different ages. The study group comprised 353 players from first-division clubs in the under (U)-14, U-15, U-17, U-20, and professional categories. The allelic and genotypic frequencies did not differ significantly in any of the categories between the group of players and the control group. This was the first study of ACE-I/D polymorphism in Brazilian soccer players.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.019
Threshold uncertainty score0.038

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.007
GPT teacher head0.218
Teacher spread0.211 · 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

Citations15
Published2016
Admission routes1
Has abstractyes

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