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Record W2005029865 · doi:10.1017/s1466252308001588

The role of dietary selenium in bovine mammary gland health and immune function

2009· review· en· W2005029865 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueAnimal Health Research Reviews · 2009
Typereview
Languageen
FieldAgricultural and Biological Sciences
TopicMilk Quality and Mastitis in Dairy Cows
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsMammary glandMastitisUdderImmune systemSeleniumBiologyImmunologyInnate immune systemOffspringImmunityDairy cattleSomatic cellMicrobiologyChemistryPregnancyCancerGenetics

Abstract

fetched live from OpenAlex

Mastitis is not only a major cause of economic losses to the dairy industry but also a major problem in ensuring the quality and safety of the milk, associated with high somatic cell counts and residues of antibiotics used for treatment. One innovative approach to protection against mastitis is to stimulate the animal's natural defense mechanisms. Technological advances in immunological research have increased our ability to exploit the immunity of the bovine mammary gland during periods of high susceptibility to disease. The trace element selenium affects the innate and the adaptive immune responses of the mammary gland through cellular and humoral activities. Substantial research has been carried out on the effect of selenium (Se) on the immune function of the mammary gland and subsequent improvement in bovine udder health and mastitis control. Levels higher than current recommendations and Se-yeast can potentially be used to enhance our capacity to modulate the physiological mechanisms of the bovine mammary gland to respond to infection. This article provides an overview of the most recent research in this 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.

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)0.014
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score0.497

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.275
GPT teacher head0.444
Teacher spread0.169 · 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