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Record W2964852131 · doi:10.3168/jds.2019-16829

Risk factors identified on arrival associated with morbidity and mortality at a grain-fed veal facility: A prospective, single-cohort study

2019· article· en· W2964852131 on OpenAlexaff
Karen A. Scott, D.F. Kelton, T.F. Duffield, D.L. Renaud

Bibliographic record

VenueJournal of Dairy Science · 2019
Typearticle
Languageen
FieldVeterinary
TopicAnimal health and immunology
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineBody mass indexProspective cohort studyHazard ratioProportional hazards modelCohortEnvironmental healthVeterinary medicineInternal medicineConfidence interval

Abstract

fetched live from OpenAlex

High levels of morbidity, mortality, and antimicrobial use are common in the veal industry. For the sustainability of the industry, it is important to address these challenges and determine factors that can be used to improve animal health and welfare. The objectives of this prospective observational cohort study were to describe the health status of calves on arrival at a grain-fed veal facility and determine characteristics that were associated with morbidity and mortality. On arrival, the calves were assessed for health abnormalities, weighed, measured for hip height and length from withers to lumbosacral junction, and had blood collected to determine serum total protein level. Body mass index (BMI) was calculated using weight on arrival divided by the sum of the calf's length from withers to lumbosacral junction and hip height. The calves were observed for 77 d after arrival, during which the producer was responsible for recording all antibiotic treatments and mortality. We built Cox proportional hazard models for morbidity and mortality variables. We created 2 morbidity models: 1 for calves that were treated <21 d after arrival at the facility, and 1 for calves that were treated during the 11 wk at the facility. From January to December 2017, 998 calves were evaluated on arrival at the veal rearing facility. A large proportion (68%) were treated with antibiotics in the first 21 d after arrival. The only explanatory variable in the final <21 d morbidity model was BMI: calves with a higher BMI had a lower hazard of being treated for disease in the first 21 d after arrival. A total of 872 calves (87%) were treated at least once over the 11-wk housing period. A calf arriving with a BMI >371.46 g/cm or a serum total protein between 5.8 and 6.2 g/dL had a lower level of morbidity during the observation period. Over the 11-wk housing period, 74 calves (7.5%) died. Calves that arrived at the facility with a fecal score of 2 or a rectal temperature between 38.9 and 39.1°C had a higher hazard of dying; calves that had a BMI of >371 g/cm were less likely to die than calves that had a BMI <330 g/cm. These results point to the importance of assessing calves on arrival at a veal facility as a measure of identifying those at high risk for morbidity and mortality.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.020
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.332
Teacher spread0.268 · 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 teacher head, 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

Citations52
Published2019
Admission routes1
Has abstractyes

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