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Record W4396806052 · doi:10.1242/jeb.246770

Tibial strains are sensitive to speed perturbations, but not grade perturbations, during running

2024· article· en· W4396806052 on OpenAlexafffund
Michael Baggaley, Ifaz T. Haider, Olivia L. Bruce, Arash Khassetarash, W. Brent Edwards

Bibliographic record

VenueJournal of Experimental Biology · 2024
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsCanadian Sport Centre PacificVancouver Island UniversityAlberta Bone and Joint Health InstituteUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPercentileTibiaStrain (injury)Stress fracturesTreadmillWork (physics)Finite element methodMathematicsSensitivity (control systems)OrthodonticsStructural engineeringMaterials scienceMedicineSimulationSurgeryComputer sciencePhysical therapyEngineeringStatisticsMechanical engineering

Abstract

fetched live from OpenAlex

A fatigue-failure process is hypothesized to govern the development of tibial stress fractures, where bone damage is highly dependent on the peak strain magnitude. To date, much of the work examining tibial strain during running has ignored uphill and downhill running despite the prevalence of this terrain. This study examined the sensitivity of tibial strain to changes in running grade and speed using a combined musculoskeletal-finite element modelling routine. Seventeen participants ran on a treadmill at ±10, ±5 and 0 deg; at each grade, participants ran at 3.33 m s-1 and at a grade-adjusted speed of 2.50 and 4.17 m s-1 for uphill and downhill grades, respectively. Force and motion data were recorded in each grade and speed combination. Muscle and joint contact forces were estimated using inverse-dynamics-based static optimization. These forces were applied to a participant-adjusted finite element model of the tibia. None of the strain variables (50th and 95th percentile strain and strained volume ≥4000 με) differed as a function of running grade; however, all strain variables were sensitive to running speed (F1≥9.59, P≤0.03). In particular, a 1 m s-1 increase in speed resulted in a 9% (∼260 με) and 155% (∼600 mm3) increase in peak strain and strained volume, respectively. Overall, these findings suggest that faster running speeds, but not changes in running grade, may be more deleterious to the tibia.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.027
GPT teacher head0.278
Teacher spread0.252 · 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

Citations9
Published2024
Admission routes2
Has abstractyes

Explore more

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