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Record W4285407972 · doi:10.1017/s1466252322000020

Acute interstitial pneumonia and the biology of 3-methylindole in feedlot cattle

2022· review· en· W4285407972 on OpenAlexafffund
Luke A. J. Haydock, R. Kent Fenton, Lauren Sergejewich, E. James Squires, Jeff Caswell

Bibliographic record

VenueAnimal Health Research Reviews · 2022
Typereview
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsAlberta Health ServicesUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of CanadaBeef Cattle Research Council
KeywordsFeedlotBeef cattleAnimal productionDiseaseAnimal husbandryAnimal scienceCattle DiseasesBovine respiratory diseasePathogenesisMedicineBiologyVeterinary medicineImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Acute interstitial pneumonia (AIP) of cattle has been recognized for many decades. While the pathogenesis and risk factors for this condition in pastured cattle are relatively well characterized, there remains a poor understanding of the disease as it occurs in intensively fed cattle such as in beef feedlots. Specifically, in pastured cattle, AIP results from excessive ruminal production of the pneumotoxicant 3-methylindole (3-MI). In feedlot cattle, the evidence to substantiate the role of 3-MI is comparatively deficient and further investigations into the cause, pathogenesis, and control are sorely needed. This review highlights our current understanding of AIP with a focus on the disease as it occurs in feedlot cattle. Additionally, it illustrates the need for further work in understanding the specific animal factors (e.g. the ruminal microbiome, and the role of concurrent diseases), management factors (e.g. animal stocking and vaccination protocols), and dietary factors (e.g. dietary supplements) that may impact the development of AIP and which are relatively unique to the feedlot setting. All stakeholders in the beef industry stand to benefit from a greater understanding of what remains a pressing yet poorly understood issue in beef production.

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)0.014
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.354
GPT teacher head0.536
Teacher spread0.182 · 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.

Study designNot applicable
Domainnot available
GenreReview

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

Citations14
Published2022
Admission routes2
Has abstractyes

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