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Record W4403463284 · doi:10.1111/eve.14062

Diagnostic approach to chronic diarrhoea in adult horses

2024· article· en· W4403463284 on OpenAlexaff
Erika Sjolin, A. C. Lack, Luis G. Arroyo

Bibliographic record

VenueEquine Veterinary Education · 2024
Typearticle
Languageen
FieldVeterinary
TopicVeterinary Equine Medical Research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsMedicineChronic diarrhoeaChronic diarrheaDiarrheaIntensive care medicineInternal medicine

Abstract

fetched live from OpenAlex

Summary Chronic diarrhoea presents a diagnostic challenge for both human physicians and equine veterinarians. There is currently no consensus in the equine veterinary literature on the definition of chronic diarrhoea. The differential list is extensive and identifying diarrhoea by pathophysiologic mechanism can help remove less likely diagnoses. Achieving a definitive antemortem diagnosis is also challenging. Results from non‐invasive diagnostics may only lead to the conclusion that inflammation is present. Cellular infiltrate, if present, may not be representative of the underlying disease. Invasive diagnostics resulting in acquisition of full‐thickness biopsies may result in a diagnosis when other methods have failed. However, there is currently minimal data correlating these findings with those from full post‐mortem examination. This article discusses the various diagnostic options and reviews the available literature on their value in evaluating currently available patients with chronic diarrhoea.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.587
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.002

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 head0.075
GPT teacher head0.411
Teacher spread0.337 · 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
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

Citations1
Published2024
Admission routes1
Has abstractyes

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