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Record W2550858863 · doi:10.2527/jam2016-1217

1217 Comparison of DX613 copper sulfate acidifier to a 5% copper sulfate footbath for prevention of digital dermatitis lesions in dairy cattle

2016· article· en· W2550858863 on OpenAlexaboutno aff
H. B. Reichenbach, Barbara Wadsworth, J. D. Clark, J.M. Bewley

Bibliographic record

VenueJournal of Animal Science · 2016
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLamenessMedicineCopper sulfateAnimal scienceDairy cattleVeterinary medicineCopperSurgeryChemistryBiology

Abstract

fetched live from OpenAlex

Digital dermatitis (DD) is an infectious disease seriously plaguing the dairy industry. The gold standard for prevention is a copper sulfate footbath. Although this method is effective, the large quantities of product required and the negative environmental impacts of bath waste necessitates a search for alternatives. The objective of this study was to compare a 2.2% copper sulfate footbath with 325.31 mL of DX613 Acidifier (treatment; GEA Farm Technologies, Naperville, IL) to a 5% copper sulfate footbath (positive control) on the frequency and severity of DD. Footbaths were delivered via a split footbath (Intra Care Foot Bath, Diamond Hoof Care LTD Alberta, Canada), measuring 32.5 cm wide by 233 cm long, allowing for 80 L of solution per side. A metal coil separated the 2 footbaths to prevent cross contamination of solutions and decrease organic matter contamination. The left side of the bath served as the positive control and the right side served as the treatment. Baths were refreshed every 2 to 3 milkings, twice weekly. The study was conducted at the University of Kentucky Coldstream Dairy from November 11, 2015 to January 20, 2016. Holstein (n = 59) cows were housed in 2 freestall barns and balanced for parity and days in milk. The cows were exposed to the solutions on leaving the parlor after morning and afternoon milkings, 5 times per week. The DD lesions were scored biweekly using a M0 to M4 scoring system. A M0 score indicated no lesion (non-active lesions); M1 indicated small lesions (active lesions); M2 indicated large and potentially severe lesions (active lesions); M3 represented healing lesions (non-active lesions); and M4 represented chronic lesions (non-active lesions). The DD lesions were further separated into active lesions or non-active lesions for statistical analysis. A Chi-Square test calculated using the FREQUENCY procedure of SAS (SAS Institute, Inc., Cary, NC) indicated no-significant difference between the two solutions (chi-square = 1.18, P = 0.56). Eleven percent of treatment cows had active lesions and 9% of positive control cows had active lesions. A McNemar's test indicated significant differences in the prevalence of lesions from the beginning to end of the study (treatment: P < 0.05, positive control: P < 0.01; Table 1). This concludes a comparable effectiveness of both solutions. Given the potential for reduced environmental impact, the DX613 Acidifier may be a viable alternative for dairy producers.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.105
GPT teacher head0.397
Teacher spread0.292 · 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 designRandomized trial
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

Citations0
Published2016
Admission routes1
Has abstractyes

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