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Record W3158280677 · doi:10.3389/fpsyg.2021.625354

Characterization of Reproductive and Morphological Variables in Female Elite Futsal Players

2021· article· en· W3158280677 on OpenAlexaff
Marcos Roberto Queiróga, Danilo Fernandes da Silva, Sandra Aires Ferreira, Vinícius Müller Reis Weber, Daniel Zanardini Fernandes, Timothy Gustavo Cavazzotto, Bruno Sérgio Portela, Marcus Peikriszwili Tartaruga, Matheus Amarante do Nascimento, Edgar Ramos Vieira

Bibliographic record

VenueFrontiers in Psychology · 2021
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMenarcheAnthropometryLuteal phaseDemographyMenstrual cyclePsychologyMenstruationFollicular phaseMedicineGynecologyEndocrinologyInternal medicineHormone

Abstract

fetched live from OpenAlex

We aimed to characterize the age of onset of training, age at menarche, menstrual periodicity, and performance perception during the menstrual cycle and examined the impact of these reproductive variables on body composition, morphology, and body weight satisfaction in Brazilian elite futsal players. The study consisted of 115 female Brazilian elite futsal players from the top national teams. Data were collected during the twentieth Women's Brazil Futsal Cup. Players were interviewed and self-reported their age of onset of training, age at menarche, menstrual periodicity, and the menstrual period, where they performed best. We also asked for what they considered to be their ideal body weight as well as information related to their training (i.e., volume and frequency). Subsequently, anthropometric measurements (i.e., body mass, height, circumferences, diameters, and skinfold thickness) were performed to estimate the body composition and determine morphological characteristics (e.g., somatotype). Fifty-nine (53.2%) players were postmenarche-trained and 52 (46.8%) were premenarche-trained. Eighteen (16.2%), 65 (58.6%), and 28 (25.2%) were classified as early, normal, and late menarche, respectively. Only 11 (9.6%) and 1 (0.9%) had irregular menstrual cycles and were amenorrheic, respectively. Seventy-three (69.5%), 23 (21.9%), and 9 (8.6%) reported that their game performance was the best at the follicular phase, menses, and luteal phase of the menstrual cycle, respectively. No associations between the four reproductive-related variables were found. Postmenarche-trained players had significant lower age at menarche and higher percentage body fat. The somatotype profile registered lower ectomorphy rate for the postmenarche-trained participants after controlling for covariates. Early menarche group presented higher sum of six skinfold thickness and endomorphy rate compared to normal and late menarche groups. No differences were found when menstrual periodicity groups and best performance groups were compared, except for higher femur width in the regular menstrual cycle group compared to the irregular one. The association between body weight satisfaction and the four reproductive-related variables were not observed. Premenarche-trained Brazilian elite futsal players had the menarche later than the postmenarche-trained athletes. Most of the participants had menarche age classified as "normal," presented "regular" menstrual cycles and perceived to perform better during the follicular phase of the menstrual cycle.

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 score0.005
Threshold uncertainty score0.010

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 head0.022
GPT teacher head0.301
Teacher spread0.279 · 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

Citations13
Published2021
Admission routes1
Has abstractyes

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