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Record W2077885565 · doi:10.1260/1747-9541.9.2.393

The Relationship between Speed and Technical Development in Young Speed Skaters

2014· article· en· W2077885565 on OpenAlexaff
Tracy L. Hillis, Shawn Holman

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2014
Typearticle
Languageen
FieldPsychology
TopicChildren's Physical and Motor Development
Canadian institutionsThe King's UniversitySt. Mary's University
Fundersnot available
KeywordsSpeed skatingAdaptation (eye)Physical developmentPsychologyPhysical medicine and rehabilitationComputer scienceSimulationDevelopmental psychologyMedicine

Abstract

fetched live from OpenAlex

The Long Term Athletic Development Plan (LTAD) defines the first ‘window of accelerated adaptation to speed’ or a ‘critical’ period of speed development as occurring during the FUNdamentals stage, age six to eight for girls and seven to nine for boys respectively. However, technical sport specific skill development is not recommended until the Learn to Train Stage. Utilizing a model of body composition, this study looks at the relationship between technical and speed development in young speed skaters ages 3 – 15. The results indicate that in both females and males, individuals with larger body composition had faster speeds but individuals with smaller body composition and with greater technical skill were as fast as or faster than those with larger body composition regardless of technical skill. The results support the conclusion that no “windows of trainability” for speed development need to exist as long as technical components are taught early to build neurological connections and fortify coordination to develop speed prepubescent, and technical development is maintained to allow skaters to adjust to increased muscular strength during pubescence and post-pubescence.

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)0.003
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 score0.029
Threshold uncertainty score0.266

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.027
GPT teacher head0.318
Teacher spread0.291 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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