MétaCan
Menu
Back to cohort
Record W3211580178 · doi:10.1123/jab.2021-0148

Regulating Movement Frequency and Speed: Implications for Lumbar Spine Load Management Strategies Demonstrated Using an In Vitro Porcine Model

2021· article· en· W3211580178 on OpenAlexaff
Jackie D. Zehr, Jessa M. Buchman-Pearle, Tyson A.C. Beach, Chad E. Gooyers, Jack P. Callaghan

Bibliographic record

VenueJournal of Applied Biomechanics · 2021
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCompression (physics)WeightingMedicineMathematicsBiomedical engineeringOrthodonticsMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The relationship between internal loading dose and low-back injury risk during lifting is well known. However, the implications of movement parameters that influence joint loading rates-movement frequency and speed-on time-dependent spine loading responses remain less documented. This study quantified the effect of loading rate and frequency on the tolerated cumulative loading dose and its relation to joint lifespan. Thirty-two porcine spinal units were exposed to biofidelic compression loading paradigms that differed by joint compression rate (4.2 and 8.3 kN/s) and frequency (30 and 60 cycles per minute). Cyclic compression testing was applied until failure was detected or 10,800 continuous cycles were tolerated. Instantaneous weighting factors were calculated to evaluate the cumulative load and Kaplan-Meier survival probability functions were examined following nonlinear dose normalization of the cyclic lifespan. Significant reductions in cumulative compression were tolerated when spinal units were compressed at 8.3 kN/s (P < .001, 67%) and when loaded at 30 cycles per minute (P = .008, 45%). There was a positive moderate relationship between cumulative load tolerance and normalized cyclic lifespan (R2 = .52), which was supported by joint survivorship functions. The frequency and speed of movement execution should be evaluated in parallel to loading dose for the management of low-back training exposures.

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 score0.773
Threshold uncertainty score0.458

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 head0.027
GPT teacher head0.306
Teacher spread0.279 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Applied BiomechanicsSame topicMusculoskeletal pain and rehabilitationFrench-language works237,207