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Record W1836378637 · doi:10.1055/s-0038-1632743

Force overlap in trotting dogs: a Fourier technique for reconstructing individual limb ground reaction force

2002· article· en· W1836378637 on OpenAlexaboutno aff
John E. A. Bertram, Rory J. Todhunter, Alwyn Williams, G. Lust, D. V. Lee

Bibliographic record

VenueVeterinary and Comparative Orthopaedics and Traumatology · 2002
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsForelimbHindlimbGround reaction forceImpulse (physics)Fourier analysisFourier transformAnatomyFourier seriesMedicineGeodesyGeometryMathematicsPhysicsMathematical analysisGeologyKinematicsClassical mechanics

Abstract

fetched live from OpenAlex

Summary Time overlap of ground reaction forces from adjacent footfalls is a pervasive problem in clinical gait analysis. When overlap occurs, splitting the fore- and hindlimb force curves at the minimum point between them underestimates hindlimb impulse and contact time. A better alternative is to reconstruct the force curves that occur in the period of overlap. A Fourier method was used to quantify the shape of hindlimb force curves in Labrador Retrievers and Greyhounds. Fourier coefficients did not differ significantly (p <0.05) between those breeds, indicating that, on average, their shapes are quite similar. The technique reported here uses an empirically determined shape that is, subsequently, scaled to the duration and magnitude of the original hindlimb force curve. A segment of this approximated force curve is then inserted in order to reconstruct the portion of the curve that was obscured by the overlap. Subtracting the reconstructed hindlimb curve, from the original force record, yields a reconstructed forelimb force curve.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.380
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.187
GPT teacher head0.340
Teacher spread0.152 · 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.

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

Citations12
Published2002
Admission routes1
Has abstractyes

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