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Record W4296765939 · doi:10.1055/s-0037-1617375

Are sound dogs mechanically symmetric at trot?

2008· article· en· W4296765939 on OpenAlexaboutno aff
GR Colborne

Bibliographic record

VenueVeterinary and Comparative Orthopaedics and Traumatology · 2008
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Orthopedics and Neurology
Canadian institutionsnot available
Fundersnot available
KeywordsStifle jointCruciate ligamentAnatomyMedicineJoint (building)Metatarsophalangeal jointsInverse dynamicsHindlimbReactionVertical axisOrthodonticsGeometryAnterior cruciate ligamentPhysicsStructural engineeringKinematicsMathematicsClassical mechanics

Abstract

fetched live from OpenAlex

Summary A two-year-old, sound Labrador Retriever was determined to be ’right hind limb dominant’ by comparison of total hind limb moments of support using inverse dynamics. Net joint moments at the hip, tarsal and metatarsophalangeal joints were larger on the right side. Vertical joint reaction forces at the stifle were larger on the right, and horizontal stifle joint reaction forces were smaller on the right. The crus segment was more cranially inclined on the right side through most of stance, but the angle of the resultant stifle joint reaction force vector against the long axis of the crus segment was identical between the right and left sides. The cranially inclined crus segment orientation on one side, coupled with the larger vertical joint reaction force, may result in an internal asymmetry in stifle joint mechanics, although the effects of this on cruciate ligament stresses remain to be determined.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0050.002

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 head0.234
GPT teacher head0.342
Teacher spread0.108 · 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 source (direct Gemma or distilled Codex), 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

Citations38
Published2008
Admission routes1
Has abstractyes

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