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Record W7033494961

Prevalence and clinical features of hypoadrenocorticism in Great Pyrenees dogs in a referred population: 11 cases

2017· article· en· W7033494961 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed Central · 2017
Typearticle
Languageen
FieldHealth Professions
TopicArtificial Intelligence in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsConfidence intervalPopulationCachexiaRetrospective cohort studyEpidemiology
DOInot available

Abstract

fetched live from OpenAlex

Naturally occurring hypoadrenocorticism (Addison’s disease) is uncommon, with an estimated prevalence in the canine population between 0.06% and 0.28%. This retrospective study evaluated the prevalence and clinical features of hypoadrenocorticism in Great Pyrenees (GP) dogs presented to the Centre Hospitalier Universitaire Vétérinaire of the University of Montreal between March 2005 and October 2014. During this period, 100 dogs were diagnosed with hypoadrenocorticism, representing 0.38% [95% confidence interval (CI): 0.26% to 0.5%] of the canine population studied. The highest prevalence was observed in GP (9.73%, 95% CI: 9.12% to 10.35%, P < 0.0001), followed by West Highland white terriers (4.66%, 95% CI: 4.24% to 5.09%, P < 0.0001), Great Danes (1.87%, 95% CI: 1.6% to 2.14%, P < 0.0001), standard poodles (1.76%, 95% CI: 1.5% to 2.02%, P = 0.0001), Saint Bernards (1.72%, 95% CI: 1.47% to 1.98%, P = 0.018), and Jack Russell terriers (1.48%, 95% CI: 1.24% to 1.72%, P = 0.003). Although most clinical features were nonspecific, Great Pyrenees dogs were more frequently presented with anemia, azotemia, and eosinophilia, or with hypotension and cachexia compared with dogs of other breeds.

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)0.006
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 score0.165
Threshold uncertainty score0.968

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
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 integrity0.0000.001
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 head0.232
GPT teacher head0.485
Teacher spread0.253 · 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
Published2017
Admission routes1
Has abstractyes

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