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Record W3033475622 · doi:10.70252/xygt9428

Momentum During a Running Competition: A Sequential Explanatory Mixed-Methods Study

2020· article· en· W3033475622 on OpenAlexaff
Vincent Gosselin Boucher, Sandra Peláez, Andrée‐Anne Parent, Jacques Plouffe, Alain Steve Comtois

Bibliographic record

VenueInternational journal of exercise science · 2020
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversité du Québec à ChicoutimiUniversité du Québec à RimouskiMcGill UniversityUniversité de MontréalCégep de RimouskiUniversité du Québec à Montréal
Fundersnot available
KeywordsMomentum (technical analysis)Competition (biology)Distance runningTime trialSelection (genetic algorithm)PsychologySample (material)Explanatory modelSample size determinationPhysical therapyEconometricsDemographyMedicineStatisticsComputer scienceMathematicsBiologyInternal medicineEconomicsMachine learningEcologyChemistryBlood pressureSociology

Abstract

fetched live from OpenAlex

International Journal of Exercise Science 13(5): 615-632, 2020. The purpose of this study was to better understand the psychological momentum (PM) in varsity cross-country competitive runners during a 3000 m selection trials. A sequential explanatory mixed methods design was used: recruitment trial race day (quantitative) and interview day (qualitative + maximal aerobic running speed [MARS]). Sample was consisted of fifteen university distance runners (n = six women [25.9 ± 7.0 years old; 22.2 ± 1.8 BMI] and nine men [23.2 ± 2.4 years old; 22.6 ± 1.6 BMI]). During the recruitment trial race, athletes’ MARS was measured and used to create a performance index (PERFI) relative to selected moments. Also, the recruitment trial race was filmed. During the interviews, the recorded film was used to support athletes in the identification of key moments of the race, as well as to discuss positive and negative PM. PM was both defined by participants and devised by three themes: psychological, physiological and psychophysiological change. A significant PERFI difference (p < 0.001) was observed between positive (97.04 ± 5.88%) and negative (108.46 ± 7.76%) moments of PM. The results of PERFI for men and women athletes were not significantly different (p = 0.118). The PERFI standard deviation for women was not correlated (r2 = 0.26, p = 0.30) with the 3000 m time trial performance, but it was significantly correlated for men (r2 = 0.94, p < 0.001). The results of the present study could help developing interventions to focus on specific elements of the momentum such as race management/strategy, the attentiveness of the runner during the race and other elements of mental and physical preparation of the athletes.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.161
Threshold uncertainty score0.316

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.032
GPT teacher head0.378
Teacher spread0.347 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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