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Record W4224210160 · doi:10.3389/fvets.2022.859858

Association Between Recycled Manure Solids Bedding and Subclinical Mastitis Incidence: A Canadian Cohort Study

2022· article· en· W4224210160 on OpenAlexafffundabout
Annie Fréchette, Gilles Fecteau, Caroline Côté, Simon Dufour

Bibliographic record

VenueFrontiers in Veterinary Science · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversité de MontréalInstitut de Recherche et de Développement en AgroenvironnementFonds de Recherche du Québec – Nature et Technologies
FundersNovalaitNatural Sciences and Engineering Research Council of CanadaAgria DjurförsäkringFonds Québécois de la Recherche sur la Nature et les TechnologiesCanadian Dairy Commission
KeywordsMastitisAnimal scienceVeterinary medicineSubclinical infectionManureSomatic cell countMedicineIncidence (geometry)BeddingLactationBiologyMathematicsInternal medicineEcologyIce calvingPregnancy

Abstract

fetched live from OpenAlex

Recycled manure solids (RMS) are increasingly used as bedding for dairy cows. However, potential impact of RMS bedding on animal health is not well described. The objective of this study was to evaluate subclinical mastitis incidence in cows housed on RMS bedding. Twenty RMS farms and a comparative group of 60 straw-bedded farms were enrolled in a 1-year longitudinal study (2018-2019). Data from 11,031 dairy cows were collected. Variations of individual somatic cell count were evaluated using three different methods. First, we compared the cow's mean lactation linear score between cows housed on the two bedding types. Then, we compared across bedding types the risk for a given cow of having a milk test with a linear score ≥ 4. Finally, we evaluated the dynamics of somatic cell count using pairs of tests within a cow. More specifically, we considered that only pairs of DHI tests where the first test yielded a linear score < 4 were at risk of an incident subclinical mastitis event. Then, we defined a newly acquired subclinical mastitis when the second test was ≥ 4. All models were adjusted for putative confounders. We could not highlight a significant association between bedding type and cow's mean lactational linear score (least square mean of 2.47 in cows from RMS farms vs. 2.37 in straw farms; 95%CI for linear score's difference: -0.20, 0.40). Furthermore, we could not find an association between bedding type and the risk of a high linear score (≥ 4). For the latter, cows housed on RMS had 0.93 times the risk of having a high linear score than straw-bedded cows (%95 CI: 0.68, 1.28). Moreover, cows on recycled manure solids farms had 0.73 time the risk of acquiring subclinical mastitis when compared to straw-bedded farms. Again, this risk was not statistically significant (%95 CI: 0.54, 1.00). In our study, RMS bedding was not associated with subclinical mastitis, as measured by somatic cell count, when compared to cows housed on a more conventional bedding, straw bedding.

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)0.002
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 score0.039
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.027
GPT teacher head0.273
Teacher spread0.246 · 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

Citations9
Published2022
Admission routes3
Has abstractyes

Explore more

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