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Record W4404482817 · doi:10.1080/1091367x.2024.2426761

Predicting Barbell Release Speed from Peak Speed in the Bench Press Throw via a Linear Position Transducer

2024· article· en· W4404482817 on OpenAlexaff
Molly C. Henneberry, Dana Agar-Newman, Seth Lenetsky, Marc Klimstra

Bibliographic record

VenueMeasurement in Physical Education and Exercise Science · 2024
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsCanadian Sport Centre PacificUniversity of Victoria
Fundersnot available
KeywordsTransducerBench pressPosition (finance)SimulationAcousticsComputer scienceMathematicsPhysicsPhysical therapyResistance trainingMedicine

Abstract

fetched live from OpenAlex

Upper body force-velocity profiles to assess musculoskeletal performance are created using release speed (RS) of the barbell in a bench press throw (BPT). A more easily obtained variable is peak speed (PS) measured by a linear position transducer. We assessed the validity of predicting RS from measured PS. One hundred and seventy-eight throws from ten male participants age (mean ± SD) 27 ± 5 yrs, mass 88 ± 13 kg with minimum one year of resistance training performed the BPT with increasing loads on a Smith machine. Correlation revealed an exponential relationship of RS = 0.26e0.9(PS), (R2 = 0.96, p < .05). We assessed predictive validity by comparing the measured RS of the barbell in each throw to the RS estimated by this formula. Bland-Altman analysis showed the 95% limit of agreement was 0.26 m∙s−1 to 0.18 m∙s−1, with a mean difference of 0.04 m∙s−1 (2.92%), determining that PS may be used to estimate RS.

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 score0.676
Threshold uncertainty score0.288

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.034
GPT teacher head0.312
Teacher spread0.278 · 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

Citations0
Published2024
Admission routes1
Has abstractyes

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