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Hoof Pathologies Influence Kinematic Measures of Dairy Cow Gait

2005· article· en· W1965429986 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Dairy Science · 2005
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaDairy Farmers of Canada
KeywordsHoofGaitSTRIDEGait cycleMedicineGait analysisDairy cattleLamenessKinematicsAnimal sciencePhysical medicine and rehabilitationBiologyAnatomySurgery

Abstract

fetched live from OpenAlex

To explore how hoof pathologies affect the gait of dairy cattle, we studied gait profiles of cows with no visible injuries (n = 17), sole lesions (n = 14), and sole ulcers (n = 7). Video recordings of dairy cows were digitized using motion analysis software to calculate 6 stride variables for each hoof. Compared with cows with sole ulcers, healthy cows walked faster (1.11 +/- 0.03 vs. 0.90 +/- 0.05 m/s, mean +/- SEM), had shorter stride durations (1.26 +/- 0.03 vs. 1.48 +/- 0.05 s), and longer strides (139.5 +/- 2.1 vs. 130.0 +/- 3.2 cm). Percentage of triple support in the gait cycle (time when cattle were supported by 3 legs) more than doubled for cows with sole ulcers compared with healthy cows (42 vs. 18%). Gait differences were likely due to cows reducing the load on an affected leg. Few differences were detected between healthy cows and those with sole lesions, perhaps because of variation in number, severity, and location of injuries. Kinematic gait analysis is a promising approach in understanding how hoof pathologies affect dairy cow gait.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.826
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.082
GPT teacher head0.348
Teacher spread0.266 · 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