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Record W4388529162 · doi:10.1093/jas/skad281.604

PSX-30 Scratching the Surface: Investigating the Nature and Potential Causes of Pruritic Cattle

2023· article· en· W4388529162 on OpenAlexaffabout
Merle S. Olson, Nick Allan, Kendall Beaugrand, Crystal Schatz, Denis Nagel, Ann Hammad, Larry Frichske, Joe Ross, Frédéric Sauvé, Dan April, Brenda Ralston, Andrea Hanson

Bibliographic record

VenueJournal of Animal Science · 2023
Typearticle
Languageen
FieldVeterinary
TopicAnimal Behavior and Welfare Studies
Canadian institutionsUniversité de MontréalChinook Regional Hospital
Fundersnot available
KeywordsHerdVeterinary medicineBeef cattleMedicineDermatologyAnimal scienceBiology

Abstract

fetched live from OpenAlex

Abstract Depending on the year, during the winter months, cattle begin to rub bare patches on their skin due to pruritus which leads to concern from cattle producers, especially the purebred breeders. Upon further investigation by veterinarians, the cause is not always caused by lice, as many may think. This study aimed to provide insight into the cause and potential prevention/treatment of pruritic beef cattle in western Canada by examining herds that met the study’s criteria of having more than 30% of the herd exhibiting pruritus. Seven herds were examined in the winter of 2023: one from Manitoba, two from Saskatchewan, and four from Alberta. Producers from each herd completed a detailed survey on treatments, nutrition, and environmental conditions and provided feed, water, and bedding samples. Within each herd, five cattle considered non-pruritic, and ten cattle considered pruritic by visual appraisal were enrolled for standard data collection consisting of documentation and photos of skin lesions localized to pruritic areas, general health clinical exam, lice exam/collection, mite exam/collection of hairs, skin hydration (corneometer), blood chemistry and vitamin/minerals, and kidney/liver enzymes for mycotoxins. A subset of the group (1 non-pruritic and 4 pruritic) was selected for advanced data collection, including dermal hypersensitivity (grass, alfalfa, grain, weeds, and molds) measured by swelling score and infrared camera temperature measurement compared with positive and negative controls, skin punch biopsies for eosinophils (IgE) and liver biopsies for copper levels. Only 21/101 cattle had lice (18 animals < 10 lice per 6.5 cm2). No significant correlation was observed between cattle with lice and being pruritic (P > 0.05). Dermal hypersensitivity was very low across both pruritic and non-pruritic cattle and was not different (P > 0.05). Skin hydration readings within animals comparing pruritic and non-pruritic areas on their body showed only one herd having significantly (P < 0.05) drier skin on pruritic locations compared with normal locations. Vitamin A, E, and copper blood analysis showed no significant difference between pruritic and non-pruritic cattle. However, liver biopsy copper levels were (P = 0.01) less in pruritic than non-pruritic cattle. Results suggest that the cause of pruritic cattle is not necessarily a result of intense lice infestations but rather multifactorial in nature, and a decision tree for producers and veterinarians should be developed to aid in determining the correct course of action to alleviate pruritic cattle in the field.

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)0.000
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 score0.117
Threshold uncertainty score0.234

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.049
GPT teacher head0.352
Teacher spread0.304 · 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

Citations0
Published2023
Admission routes2
Has abstractyes

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