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Record W3185910696 · doi:10.3168/jds.2020-19839

Standing behavior and sole horn lesions: A prospective observational longitudinal study

2021· article· en· W3185910696 on OpenAlexaff
Hanna Eriksson, Ruan R. Daros, M.A.G. von Keyserlingk, Daniel M. Weary

Bibliographic record

VenueJournal of Dairy Science · 2021
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsInterquartile rangeAnimal scienceIce calvingMedicineHerdLactationBiologyPregnancySurgery

Abstract

fetched live from OpenAlex

Studies performed on individual research farms have reported that dairy cattle developing sole hemorrhages or sole ulcers in peak to mid lactation spent more time standing during the weeks around calving. The aim of this prospective observational longitudinal study was to evaluate whether this relationship is evident in commercial dairy herds. A convenience sample of 8 herds were visited every other week, and animals without previous severe horn lesions and deemed sound at 4 to 8 wk before calving were enrolled. Standing behavior was measured with data loggers attached to a rear leg, and standing time and duration of the longest standing bout were determined for each cow. Standing behavior was summarized into 3 periods: before (d -14 to -2), around (d -1 to 1), and after (d 2 to 14) calving. Average daily standing time and average daily longest standing bout were determined for each cow and period. Average daily standing time was normally distributed, with a mean ± standard deviation of 12.1 ± 1.6, 14.4 ± 2.2, and 13.8 ± 1.7 h/d for the 3 periods, respectively. Average daily longest standing bout was right skewed with a median of 3.6 h/d [interquartile range (IQR): 3.0 to 4.3; range: 1.7 to 12.1], 3.9 h/d (IQR: 3.1 to 4.8; range: 1.3 to 11.5), and 3.7 (IQR: 3.2 to 4.4; range: 1.5 to 11.7) h/d before, around, and after calving, respectively. Hoof trimming was performed 8 to 12 wk postpartum; hoof lesion data were summarized per cow, and the most serious injury of each type of lesion was noted. Sole hemorrhages or sole ulcers were found in 25 of 256 cows. Mixed-effect logistic regression models with herd as random effect were used to analyze the risk of developing sole hemorrhages and sole ulcers, using animals without hoof lesions as reference category. Separate models were fitted for the 2 standing behaviors, and for the periods before, around, and after calving. Change in standing behavior from before to after calving was also analyzed. Body condition score at calving, body condition score loss in early lactation, milk yield, parity, and days in milk at trimming were included as covariates. In this study, no evidence for an association was found between sole hemorrhages and sole ulcers and standing behavior before or around calving. Longer standing time and longer standing bouts after calving were associated with increased odds of developing sole hemorrhages and sole ulcers, as was an increase in standing bout duration from before to after calving. Animals with sole horn or white line lesions had higher unconditional sample odds of becoming lame (odds ratio = 2.5) and severely lame (odds ratio = 11.7) after calving, compared with animals with no registered lesions at trimming. Multiparous animals had higher lameness incidence, both before and after calving. Avoiding practices that exacerbate increases in standing time and standing bout duration in early lactation may reduce the incidence of sole hemorrhages and sole ulcers.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.001
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 head0.196
GPT teacher head0.406
Teacher spread0.210 · 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

Citations7
Published2021
Admission routes1
Has abstractyes

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