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Record W4401997353 · doi:10.1080/02640414.2024.2394746

A methodological proof-of-concept of the teeter-totter effect

2024· article· en· W4401997353 on OpenAlexaff
Ashna Subramanium, Jordyn Vienneau, Sandro Nigg, Benno M. Nigg

Bibliographic record

VenueJournal of Sports Sciences · 2024
Typearticle
Languageen
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsProof of conceptPsychologyComputer science

Abstract

fetched live from OpenAlex

The Nike Vaporfly 4% (VP4) shoe is popular due to its unique design and reported performance benefits. However, the underlying mechanisms responsible for the improvements remain unclear. One proposed mechanism is the teeter-totter effect. This study aimed to 1) experimentally test the teeter-totter theory by estimating the teeter-totter moment (MTT) in the VP4 compared to a flat shoe (CONTROL) and 2) quantify the change in the anterior-posterior position of the centre of pressure (Δxa-p) in the VP4 compared to the CONTROL. Plantar pressures and high-speed video were recorded from 15 runners in two shoe conditions. The VP4 generated a larger propulsion moment, MP, (∫MPdt = 90.46 ± 38.87 Nms; p < 0.001, d = 1.95), suggesting the presence of an MTT in the VP4 (∫MTTdt = 57.16 ± 24.35 Nms) when compared to the CONTROL (∫MPdt = 33.30 ± 14.52 Nms). Δxa-p was greater in the VP4 (Δxa-p = 9.48 ± 6.08 mm; p < 0.001, d = 2.07) compared to the CONTROL (Δxa-p = 0.54 ± 0.67 mm). This study provides a methodological proof-of-concept for the teeter-totter theory. The findings highlight the possibility of a teeter-totter effect resulting in greater heel propulsion while running in an AFT shoe construction, assuming a constant muscle moment and pivot point.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.778
Threshold uncertainty score0.111

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 head0.041
GPT teacher head0.308
Teacher spread0.267 · 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 designBench or experimental
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

Citations8
Published2024
Admission routes1
Has abstractyes

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