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Record W2152485092 · doi:10.1080/14763140701683007

An examination of slo-pitch pitching trajectories

2008· article· en· W2152485092 on OpenAlexaff
Tom Wu, Pierre Gervais

Bibliographic record

VenueSports Biomechanics · 2008
Typearticle
Languageen
FieldEngineering
TopicSports Dynamics and Biomechanics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBall (mathematics)VideographyAerodynamicsMechanicsAngular velocityProjectilePhysicsGeodesyMathematicsGeometryGeologySimulationClassical mechanicsEngineering

Abstract

fetched live from OpenAlex

Many slo-pitch coaches and players believe that generating spin on a ball can affect its trajectory. The influence of air resistance on a ball that is thrown at a moderate speed and spin is unclear. The aim of this study was to examine the influence of spin on the ball's trajectory in slo-pitch pitching using both experimental results and ball flight simulations. Fourteen pitchers participated in the study, each of whom threw five backspin and topspin pitches each. Data were collected using standard three-dimensional videography. The horizontal velocity, vertical velocity, angular velocity, release height, and horizontal displacement of the backspin pitches were significantly higher than those of the topspin pitches. The ball flight simulations were developed to examine the influence of the ball spin, and it was concluded that the spin of the ball had a significant effect on the ball's vertical and horizontal displacements. Furthermore, our results suggest that a backspin pitch that reaches the maximum height allowable and lands in the front edge of the strike zone has the steepest slope. The present results add to our understanding of projectile motion and aerodynamics.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.197
Teacher spread0.188 · 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 source (direct Gemma or distilled Codex), 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

Citations10
Published2008
Admission routes1
Has abstractyes

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