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Record W3158283571 · doi:10.21423/aabppro20084493

Use of Lung Biopsy to Determine Early Lung Pathology and Its Association with Health and Production Outcomes in High-Risk Feedlot Steers

2008· article· en· W3158283571 on OpenAlexaff
Brandy A. Burgess, S. Hendrick, Colleen M Pollock, Calvin W. Booker, G. Kee Jim, Sameeh M. Abutarbush

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2008
Typearticle
Languageen
FieldImmunology and Microbiology
TopicMicrobial infections and disease research
Canadian institutionsAlberta Health ServicesUniversity of Saskatchewan
Fundersnot available
KeywordsFeedlotLung biopsyLungMedicineBiopsyPathologyInternal medicineBiologyAnimal science

Abstract

fetched live from OpenAlex

The purposes of this study were to determine if lung biopsy can be used to characterize pulmonary pathology at feedlot arrival and in sick calves within the first 30 days on feed; to determine if lung pathology is associated with health and production outcomes; and to determine the microbiological agents associated with early lung pathology using lung biopsy.

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)0.002
metaresearch head score (Gemma)0.004
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.019
GPT teacher head0.272
Teacher spread0.252 · 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
Published2008
Admission routes1
Has abstractyes

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