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Record W4399222416 · doi:10.3168/jds.2023-24610

Use of rumination time in health risk assessment of prepartum dairy cows

2024· article· en· W4399222416 on OpenAlexaff
M.G.S. Santos, N. Antonacci, Chantel Van Dorp, B. Mion, Dan Tulpan, E.S. Ribeiro

Bibliographic record

VenueJournal of Dairy Science · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicReproductive Physiology in Livestock
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsRuminationDairy cattleAnimal scienceObstetricsFood scienceChemistryMedicineBiology

Abstract

fetched live from OpenAlex

The objectives of this observational cohort study were to evaluate the associations of rumination time (RT) in the last week of pregnancy with transition cow metabolism, inflammation, health, and subsequent milk production, reproduction, and culling. Pregnant nulliparous (n = 199) and parous (n = 337) cows were enrolled 21 d before expected calving. Rumination time and physical activity were monitored automatically by sensors from d -21 to 15 relative to calving. Blood samples were collected on d -14, -5, 4, 8, and 12 ± 1 relative to calving. Diagnoses of clinical health problems were performed by researchers from calving to 15 DIM. In classification 1, cows were ranked based on average daily RT in the last week of pregnancy and classified into terciles as short RT (SRT), moderate RT (MRT), or long RT (LRT) for association analyses. In classification 2, RT deviation from the parity average was used in a receiver operating characteristic curve to identify the best threshold to predict postpartum clinical disease. Cows were then classified as above the threshold (AT) or below the threshold (BT). Compared with cows with LRT, cows with SRT had greater serum concentrations of nonesterified fatty acids (0.47 vs. 0.40 ± 0.01 mmol/L), BHB (0.58 vs. 0.52 ± 0.01 mmol/L), and haptoglobin (0.22 vs. 0.18 ± 0.008 g/L) throughout the transition period, and reduced concentrations of glucose, cholesterol, albumin, and magnesium in a time-dependent manner. Parous cows with SRT had higher odds of postpartum clinical disease (adjusted odds ratio [AOR] = 3.7; 95% CI: 2.1-6.4), lower odds of pregnancy by 210 DIM (AOR = 0.34; 95% CI = 0.15-0.75), and lower milk production (46.9 vs. 48.6 ± 0.5 kg/d) than parous cows with LRT. Deviation in prepartum RT had good predictive value for clinical disease in parous cows (area under the curve = 0.65; 95% CI = 0.60-0.71) but not in nulliparous (area under the curve = 0.51; 95% CI = 0.42-0.59). Separation of parous cows according to the identified threshold (≤-53 min from the parity average) resulted in differences in serum concentrations of nonesterified fatty acids (AT = 0.31 ± 0.006, BT = 0.38 ± 0.014 mmol/L), BHB (AT = 0.49 ± 0.008, BT = 0.53 ± 0.015 mmol/L), and globulin (AT = 32.3 ± 0.3, BT = 34.8 ± 0.5 g/L) throughout the transition period, as well as in serum cholesterol, urea, magnesium, albumin, and haptoglobin in a time-dependent manner. Below threshold parous cows had higher odds of clinical disease (AOR = 3.7; 95% CI = 2.1-6.4), reduced hazard of pregnancy (adjusted hazard ratio = 0.64, 95% CI: 0.47-0.89), greater hazard of culling (adjusted hazard ratio = 2.1, 95% CI: 1.2-3.6), and lower milk production (46.3 ± 0.7 vs. 48.5 ± 0.3 kg/d). External validation using data from 153 parous cows from a different herd and the established threshold in RT deviation (≤-53 min) resulted in similar predictive value, with the odds of postpartum disease 2.4 times greater in BT than AT (37.5% vs. 20.1%). In conclusion, RT in the week preceding calving was a reasonable predictor of postpartum health and future milk production, reproduction, and culling in parous cows but not in nulliparous cows.

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 score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.035
GPT teacher head0.315
Teacher spread0.281 · 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".

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Citations3
Published2024
Admission routes1
Has abstractyes

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