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Record W3137932068 · doi:10.21423/aabppro20094352

Evaluation of Thoracic Ultrasonography as a Diagnostic and Prognostic Tool for Early Bovine Respiratory Disease of Feedlot Calves in Western Canada

2009· article· en· W3137932068 on OpenAlexaffabout
Calvin W. Booker, Colleen M Pollock, Sameeh M. Abutarbush, A. R. Vogstad, G. Kee Jim, Sherry J. Hannon

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2009
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsAlberta Health Services
Fundersnot available
KeywordsFeedlotBovine respiratory diseaseMedicineBeef cattleUltrasonographyDiseaseAnimal scienceIntensive care medicineVeterinary medicineInternal medicineSurgeryBiologyImmunology

Abstract

fetched live from OpenAlex

It is generally accepted that early recognition and treatment of bovine respiratory disease (BRD) improves both prognosis and outcomes, while delayed diagnosis and treatment may result in treatment failure. Methods used to detect BRD in feedlot cattle include the assessment of animal demeanor and behavior by trained feedlot workers ("pen checkers") and evaluation oftransrectal temperature. The serial use of these two methods is currently the most practical, economically feasible, and common means of detecting BRD in feedlot cattle. However, recognized limitations of these methods may result in cattle without BRD being treated unnecessarily, while animals with BRD may remain undetected or be subject to delayed detection, all of which have adverse animal well-being and economic implications.
 This project investigated the use of thoracic ultrasonography (US) as a diagnostic tool for the assessment of early BRD in feedlot cattle, and evaluated associations between US findings and subsequent animal health and production outcomes.

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)0.001
metaresearch head score (Gemma)0.007
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 score0.079
Threshold uncertainty score0.982

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.018
GPT teacher head0.314
Teacher spread0.296 · 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

Citations0
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueAmerican Association of Bovine Practitioners Conference ProceedingsSame topicMicrobial infections and disease researchFrench-language works237,207