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Record W2261146072 · doi:10.3168/jds.2016-11125

Investigation of dairy cattle ease of movement on new methyl methacrylate resin aggregate floorings

2016· article· en· W2261146072 on OpenAlexafffund
N. Franco-Gendron, Renée Bergeron, W. Curilla, S. Conte, T.J. DeVries, E. Vasseur

Bibliographic record

VenueJournal of Dairy Science · 2016
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsMcGill UniversityAgriculture and Agri-Food CanadaUniversity of Guelph
FundersGovernment of AlbertaUniversité de SherbrookeAgriculture and Agri-Food CanadaUniversity of GuelphMcGill UniversityUniversité LavalRicoh Americas Corporation
KeywordsSTRIDEKinematicsSwingMathematicsNatural rubberAggregate (composite)GaitAnimal scienceEnvironmental scienceComposite materialPhysical medicine and rehabilitationMaterials scienceMedicineEngineeringBiologyPhysics

Abstract

fetched live from OpenAlex

Freestall dairy farms commonly present issues with cattle slips and falls caused by smooth flooring and manure slurry. This study examined the effect of 4 new methyl methacrylate (MMA) resin aggregate flooring types (1-4) compared with rubber (positive) and concrete (negative control) on dairy cow (n=18) ease of movement when walking on straight and right-angled corridors. Our hypothesis was that cow ease of movement when walking on the MMA surfaces would be better than when walking on traction milled concrete, and at least as good as when walking on rubber. Cattle ease of movement was measured using kinematics, accelerometers, and visual observation of gait and associated behaviors. Stride length, swing time, stance time, and hoof height were obtained from kinematic evaluation. Acceleration and asymmetry of variance were measured with accelerometers. Locomotion score and behaviors associated with lameness, such as arch back, head bob, tracking up, step asymmetry, and reluctance to bear weight were visually observed. Stride length, swing time, stance time, and the number of steps taken were the only variables affected by flooring type. Differences between flooring types for these variables were tested using a generalized linear mixed model with cow as a random effect, week as a random block factor, and flooring type as a fixed effect. Multiple comparisons with a Scheffé adjustment were done to analyze differences among flooring types. Stride length was 0.14 m longer (better) on rubber when compared with concrete, and 0.11 and 0.17 m shorter on MMA 1 and 2 compared with rubber. On MMA 3 and 4, stride length did not differ from either rubber or concrete. Swing time was 0.04 s shorter (worse) on MMA 1 than on rubber, but did not differ from any other flooring. Stance time was 0.18 s longer (worse) on MMA 2 when compared with rubber, but it did not differ from any other treatment. The number of steps was higher on MMA 4 compared with rubber (4.57 vs. 3.95 steps), but did not differ from any other treatment. Of all the MMA floors tested, MMA 3 was the only one that was consistently as good as rubber (positive control). All 4 MMA floors never differed from concrete (negative control) in any of the ease of movement variables measured. These results suggest that MMA 3 may improve cow ease of movement, compared with the other MMA floors, but more research is required to confirm these findings.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.078
GPT teacher head0.334
Teacher spread0.256 · 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

Citations14
Published2016
Admission routes2
Has abstractyes

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