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Record W7094606998

Cardiovascular and perceptual stress of female basketball
\nreferees during women’s international matches

2017· article· W7094606998 on OpenAlexaboutno aff

Bibliographic record

VenueResearchOnline at James Cook University (James Cook University) · 2017
Typearticle
Language
FieldEconomics, Econometrics and Finance
TopicDiverse Scientific and Economic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsBasketballHeart rateQuarter (Canadian coin)Match playElitePerceptionAnalysis of variance
DOInot available

Abstract

fetched live from OpenAlex

Background: The current aims were to determine body composition (BC), and heart rate (HR) and rating of perceived effort (RPE) responses by female basketball referees during elite international competition.
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\nMethods: During the precompetition, BC via skinfolds was assessed in 10 referees (38±3 yr) who officiated 11 matches. Referees’ HR and exercise intensity (based upon maximum HR, HRmax) were recorded during each quarter of each match and RPE assessed postmatch. Differences between quarters were examined via repeated measures ANOVA while correlations between RPE, HR, BC and experience were also considered.
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\nResults: The average match HR was 86.2±5.0 HRmax with this being significantly lower during the 4th quarter compared to the 1st (P=0.018)and 2nd quarters (P=0.001), and significantly lower during the 3rd compared to the 2nd quarter (P=0.005). The average postmatch RPE was 12.5±1.6 with significant inverse correlations identified between post-match RPE and exercise intensity (average HR, %HRmax). Significant correlations were identified between the average match HR and BC (0.608, P=0.016), and experience (-0.653, P=0.008).
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\nConclusions: The current investigation has demonstrated that elite female basketball referees experience significant cardiovascular and perceptual stress during international matches that may be influenced by referee experience and BC. These unique characteristics may aid in referee preparation for elite competition.

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 categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.791
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.000
Science and technology studies0.0030.004
Scholarly communication0.0010.002
Open science0.0030.006
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0090.001

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 head0.037
GPT teacher head0.212
Teacher spread0.175 · 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; both teacher heads agree on what is shown here.

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
Published2017
Admission routes1
Has abstractyes

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