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Record W2294101407 · doi:10.1080/02640414.2016.1157262

The influence of golf shaft stiffness on grip and clubhead kinematics

2016· article· en· W2294101407 on OpenAlexaff
Sasho MacKenzie, Daniel E. Boucher

Bibliographic record

VenueJournal of Sports Sciences · 2016
Typearticle
Languageen
FieldEngineering
TopicSports Dynamics and Biomechanics
Canadian institutionsSt. Francis Xavier University
Fundersnot available
KeywordsKinematicsStiffnessDeflection (physics)Rotation (mathematics)Structural engineeringOrthodonticsGeologyMathematicsPhysicsEngineeringMedicineGeometry

Abstract

fetched live from OpenAlex

The purpose of this study was to investigate the influence of shaft stiffness on grip and clubhead kinematics. Two driver shafts with disparate levels of stiffness, but very similar inertial properties, were tested by 33 golfers representing a range of abilities. Shaft deflection data as well as grip and clubhead kinematics were collected from 14 swings, with each shaft, for each golfer using an optical motion capture system. The more flexible shaft (R-Flex) demonstrated a higher contribution to clubhead speed from shaft deflection dynamics (P < .001), but was also associated with significantly less grip angular velocity at impact (P = .001), resulting in no significant difference in clubhead speed (P = .14). However, at the individual level, half of the participants demonstrated a significant difference in clubhead speed between shafts. The more flexible shaft was also associated with significantly different magnitudes of head rotation relative to the grip. More specifically, both bend loft (P < .001) and bend lie (P < .001) were greater for the R-Flex shaft, while bend close (P = .017) was greater for the stiffer (X-Flex) shaft. However, changes in grip orientation resulted in no significant differences in face orientation, between the shafts, at impact.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.121

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 communication0.0000.000
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 head0.007
GPT teacher head0.218
Teacher spread0.211 · 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

Citations17
Published2016
Admission routes1
Has abstractyes

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