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Record W1963681702 · doi:10.1080/02640410400021393

Timing of ball release in overarm throws affects ball speed in unskilled but not skilled individuals

2005· article· en· W1963681702 on OpenAlexaff
E Jegede, S. Watts, Lawrence W. Stitt, J. Hore

Bibliographic record

VenueJournal of Sports Sciences · 2005
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsWestern University
Fundersnot available
KeywordsBall (mathematics)KinematicsSimulationThrowingMathematicsPhysical medicine and rehabilitationComputer sciencePhysicsGeometryEngineeringMedicineAeronautics

Abstract

fetched live from OpenAlex

We tested the hypothesis that variability in the timing of ball release in overarm throws affects ball speed. Nine unskilled and six skilled throwers made 30 throws fast and accurately from a sitting and standing position. Angular positions of finger and arm segments were recorded with search-coils at 1000 Hz; ball speed was measured with a radar gun. The time of ball release from the fingertips was measured with respect to seven arm kinematic reference points. Mean timing windows for ball release were 28 ms for unskilled throwers and 7 ms for skilled throwers. Mixed-model analyses of variance showed that a there was a statistically significant relationship between ball speed and the timing of ball release in unskilled throwers, but not in skilled throwers. This was presumably due to the difference in variability of the timing of ball release between the two groups. In contrast, skilled throwers showed a relationship between ball speed and peak forearm angular velocity (one measure of arm speed). We conclude that although variability in the timing of ball release can affect ball speed, this is only a major factor in unskilled throwers. When skilled throwers throw fast, variability in ball speed is due to variability in arm speed.

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 score0.010
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
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 head0.029
GPT teacher head0.309
Teacher spread0.280 · 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

Citations23
Published2005
Admission routes1
Has abstractyes

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