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Record W3198007825 · doi:10.21423/aabppro20143703

Predicting prognosis of left displaced abomasal corrective surgery

2014· article· en· W3198007825 on OpenAlexaff
Jennifer L Reynen, S.J. LeBlanc, D.F. Kelton, T.F. Duffield

Bibliographic record

VenueAmerican Association of Bovine Practitioners Conference Proceedings · 2014
Typearticle
Languageen
FieldMedicine
TopicIntestinal and Peritoneal Adhesions
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineAbomasumCullingGlutamate dehydrogenaseInternal medicineSurgeryIncidence (geometry)GastroenterologyVeterinary medicineBiologyGlutamate receptorHerd

Abstract

fetched live from OpenAlex

The incidence rate of left displaced abomasum (LDA) in North America is commonly 3 to 7% of calvings. Of these cases, 12 to 17% are culled or die within 30 days of surgery. There have been numerous studies focused on predicting prognosis for right displaced abomasal corrective surgery; however, fewer studies focus on LDA surgeries. These studies tend to measure only a few parameters (i.e. blood analysis) and none focus on concurrent disease or physical exam at diagnosis. Croushore et al (2013) reported that cows that were not ketotic at diagnosis (BHBA<1.2mmol/L) were at 2.5 times greater risk of being culled within 30 days than ketotic cows. Various studies have also demonstrated that elevated aspartate aminotransferase, glutamate dehydrogenase, ornithine carbamoyl transferase, bilirubin, urea, Ca, K, and Mg were associated with an increased risk of unfavorable outcomes. The objective of this research was to determine if patient survival (or culling) within 60 days after surgery could be predicted from the physical exam findings, concurrent disease status, and a biochemical profile from a blood sample obtained at the time of LDA diagnosis.

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 score0.028
Threshold uncertainty score0.857

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.013
GPT teacher head0.264
Teacher spread0.251 · 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
Published2014
Admission routes1
Has abstractyes

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