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Record W2040206393 · doi:10.3168/jds.2010-4032

Association of standing and lying behavior patterns and incidence of intramammary infection in dairy cows milked with an automatic milking system

2011· article· en· W2040206393 on OpenAlexafffund
T.J. DeVries, J. Deming, Jack Rodenburg, Guy Séguin, K.E. Leslie, Herman W. Barkema

Bibliographic record

VenueJournal of Dairy Science · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsDairy Farmers of OntarioUniversity of CalgaryUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsMilkingLyingAssociation (psychology)Incidence (geometry)MastitisAutomatic milkingDairy cattleAnimal scienceBiologyMedicineMathematicsPsychologyLactationGeneticsPathology

Abstract

fetched live from OpenAlex

The standing and lying behavior patterns of dairy cows, particularly the length of time cows spend standing after milking, have the potential to influence the incidence of intramammary infection (IMI). The objectives were to describe the standing and lying behavior patterns of cows milked with an automatic milking system (AMS) and to determine how these patterns relate to the incidence of IMI. One hundred and eleven lactating Holstein dairy cows were monitored over a 4-mo period. These cows were kept in a sand-bedded freestall barn with 2 pens, each with a free cow traffic AMS. Feed was delivered once daily, and pushed up 2 to 3 times daily. Quarter milk samples were collected for bacteriological culture from each cow once every 4 wk. A new IMI was defined as a positive culture sample following a negative culture. For 7 d before each of the last 3 milk samplings, standing and lying behavior, and times of milking and feed manipulation (feed delivery and push up) were recorded. Daily lying time and lying bout length were negatively related with milk yield (r=-0.23 and -0.20, respectively) and milking frequency (r=-0.32 and -0.20, respectively); milk yield was positively related to milking frequency (r=0.58). Feed manipulation near the time cows were milked (1h before 2h after) resulted in the longest post-milking standing times (mean=86 min; 95% confidence interval=78, 94 min), whereas feed manipulation occurring outside that time frame resulted in shorter post-milking standing times. Over the study period, 171 new IMI were detected. Of these new IMI detected, those caused by coagulase-negative staphylococci were the only ones associated with post-milking standing time; as post-milking standing time increased past 2.5h after milking, the odds of acquiring a new IMI tended to also increase. In summary, standing and lying behavior patterns of cows milked with an AMS were affected by both feed manipulation and their milking activity. Further, the post-milking standing time of cows milked with an AMS can be managed by providing fresh feed, as well as by pushing up feed, frequently throughout the day. Finally, cows that spend long periods of time (>2.5h) standing following milking may be at higher risk of acquiring a new CNS IMI.

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 score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.033
GPT teacher head0.253
Teacher spread0.220 · 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

Citations47
Published2011
Admission routes2
Has abstractyes

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