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Record W2277917760 · doi:10.1080/02701367.2015.1124972

Locomotor, Heart-Rate, and Metabolic Power Characteristics of Youth Women's Field Hockey: Female Athletes in Motion (FAiM) Study

2016· article· en· W2277917760 on OpenAlexaffabout
Jason D. Vescovi

Bibliographic record

VenueResearch Quarterly for Exercise and Sport · 2016
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsField hockeyAthletesHeart ratePsychologyMathematicsPhysical therapyMedicineInternal medicineFootballGeography

Abstract

fetched live from OpenAlex

PURPOSE: The purpose of this study was to quantify the locomotor, heart-rate, and metabolic power characteristics of high-level youth female field hockey matches. METHOD: Players from the U21 and U17 Canadian women's national teams were monitored during a 4-match test series using Global Positioning System technology. Position (forward, midfielder, defender) and age-group (U21, U17) comparisons were made using 2-way analyses of variance. RESULTS: Forwards played 12 min to 22 min fewer than midfielders and defenders and consequently had lower amounts of total, low-intensity, and moderate-intensity distances. Yet, forwards covered similar amounts of high-intensity running and sprinting distances despite the deficit in playing time. Only 10% to 15% of total distance was characterized by high-intensity running and sprinting, yet the majority of time was spent above 90% maximum heart rate. The distances in high, elevated, and maximal metabolic power categories were greater for U21 than U17 players. Yo-Yo Intermittent Recovery Test performance was related to high-intensity running and maximal metabolic power distance. CONCLUSIONS: The current findings highlight positional specificity as well as developmental gaps between age groups for youth female field hockey matches. These match characteristics should be used to assist in establishing appropriate training strategies through the developmental pathway and to assist player achievement to higher standards.

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)0.002
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 score0.098
Threshold uncertainty score0.383

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.037
GPT teacher head0.331
Teacher spread0.293 · 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

Citations21
Published2016
Admission routes2
Has abstractyes

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