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Record W3111636059 · doi:10.3168/jds.2020-19215

The effect of Cryptosporidium parvum, rotavirus, and coronavirus infection on the health and performance of male dairy calves

2020· article· en· W3111636059 on OpenAlexaff
D.L. Renaud, C. Rot, J. A. Marshall, M.A. Steele

Bibliographic record

VenueJournal of Dairy Science · 2020
Typearticle
Languageen
FieldMedicine
TopicViral gastroenteritis research and epidemiology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsCryptosporidium parvumFecesBovine coronavirusRotavirusBiologyVeterinary medicineAnimal scienceCryptosporidiumWeaningMedicineVirologyMicrobiologyCoronavirus disease 2019 (COVID-19)Internal medicineVirus

Abstract

fetched live from OpenAlex

The objective of this prospective cohort study was to investigate the effect of bovine coronavirus (BCoV), bovine rotavirus (BRoV), and Cryptosporidiumparvum on dairy calf health and performance and to determine the prevalence of these pathogens. A total of 198 male dairy calves housed at a grain-fed veal facility were examined from June 11, 2018, to October 9, 2018. Calves were fed milk replacer twice daily and housed individually until weaning at 56 d. Once weaned, calves were moved into groups of 5 until they were moved to a finishing facility at 77 d. At the grain-fed veal facility, calves were scored for fecal consistency for the first 28 d and had fecal samples taken on arrival and at 7 and 14 d. Fecal samples were frozen and submitted to a commercial laboratory, where they were tested for BCoV, C.parvum, and 2 groups of BRoV: group A (BRoV A) and group B (BRoV B). Calves were weighed on arrival and at 14, 49, 56, and 77 d using a digital body scale. Treatments for disease and mortalities that occurred over the 77 d were also recorded. Statistical models, including Cox proportional hazards and repeated measures models, were built to determine the effect of infection with 1 of the pathogens. Over the 3 sampling points, 151 (85.8%), 178 (94.2%), 3 (1.5%), and 97 (57.4%) calves tested positive at least once for BCoV, BRoV A, BRoV B, and C.parvum, respectively. The source of the calves and the level of serum total protein measured on arrival were associated with testing positive for a pathogen. Calves that tested positive for C.parvum had an increased proportion of days with diarrhea and severe diarrhea; calves that tested positive for BCoV and BRoV A had an increased proportion of days with severe diarrhea. In addition, calves that tested positive for C.parvum had a higher hazard of being treated for respiratory disease. With respect to body weight, calves that had diarrhea or severe diarrhea had lower body weight at 49, 56, and 77 d. Specifically, calves that had an increased proportion of days with diarrhea showed a reduction in weight gain of up to 15 kg compared to calves without diarrhea. Calves that tested positive for C.parvum had a lower body weight at 49, 56, and 77 d; calves that tested positive for BCoV had a lower body weight at 56 and 77 d. This study demonstrates that the prevalence of BCoV, BRoV A, and C.parvum infection is high in this population of calves and has significant effects on the occurrence of diarrhea and body weight gain. Future studies should evaluate approaches for minimizing the effect of infection with these pathogens to improve the welfare, health, and productivity of dairy calves.

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 score0.008
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.038
GPT teacher head0.339
Teacher spread0.301 · 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

Citations29
Published2020
Admission routes1
Has abstractyes

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