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Record W2027042289 · doi:10.3168/jds.2013-6815

Herd- and cow-level risk factors associated with subclinical mastitis in dairy farms from the High Plains of the northern Antioquia, Colombia

2014· article· en· W2027042289 on OpenAlexaff
Nicolás Ramírez, G.P. Keefe, Ian R. Dohoo, Javier Sánchez, Ofelia Arroyave, Juan Manuel Cerón, Marlly Leana Amariles Jaramillo, Luis Palacio

Bibliographic record

VenueJournal of Dairy Science · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsUniversity of Prince Edward Island
Fundersnot available
KeywordsUdderMastitisMilkingHerdBreedSomatic cell countCalifornia mastitis testVeterinary medicineMedicineAnimal scienceIce calvingBiologyLactationPregnancy

Abstract

fetched live from OpenAlex

Mastitis is the main disease entity affecting dairy farms in the Colombian High Plains of northern Antioquia, Colombia. However, no previous epidemiologic studies have determined the characteristics that increase the risk of infection in this region, where manual milking is still the prevailing system of milking. A 24-mo longitudinal study was designed to identify the predominant mastitis pathogens and important herd- and cow-level risk factors. Monthly visits were made to 37 commercial dairy farms to collect herd- and cow-level data and milk samples. Herd size varied from 6 to 136 cows (mean 37.0, median 29). Herd-level factors included type of milking system (manual or mechanical) and a range of management practices recommended by the National Mastitis Council (Madison, WI) to prevent mastitis. Individual cow-level risk factors included parity, stage of lactation, breed, udder hygiene, and lameness. A logistic regression analysis was used to investigate associations between herd- and cow-level risk factors with the presence of subclinical mastitis and infection caused by Streptococcus agalactiae at the quarter level. A quarter was considered to have subclinical mastitis if it had a positive California Mastitis Test and was subsequently confirmed to have a somatic cell count of ≥200,000 cells/mL. Any cow with one or more quarters with subclinical mastitis was considered to have subclinical mastitis at the cow level. Using 17,622 cow observations, the mean prevalence of subclinical mastitis at the cow level was 37.2% (95% confidence interval: 31.2, 43.3) for the first month and did not substantially change throughout the study. The predominant microorganisms isolated from quarters meeting the subclinical mastitis definition were contagious pathogens, including Strep. agalactiae (34.4%), Corynebacterium spp. (13.2%), and Staphylococcus aureus (8.0%). Significant variables associated with subclinical mastitis risk at the quarter level included being a purebred Holstein cow, higher parity, and increased months in milk. Variables that were protective for mastitis risk included being a crossbreed cow and adequate premilking udder hygiene. Significant variables associated with Strep. agalactiae infection were higher parity, increased months in milk, and manual milking. Variables that were protective were postmilking teat dipping and adequate cleaning of the udder. The results highlight the importance of hygiene practices in contagious mastitis control in manually milked herds.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.215
Threshold uncertainty score0.428

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.040
GPT teacher head0.241
Teacher spread0.201 · 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

Citations67
Published2014
Admission routes1
Has abstractyes

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