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Record W4241798286 · doi:10.1002/9781119511816.ch18

Cardiovascular Diseases

2021· other· en· W4241798286 on OpenAlexaff
Hugues Beaufrère, Marina L. Brash

Bibliographic record

Venuenot available
Typeother
Languageen
FieldImmunology and Microbiology
TopicBird parasitology and diseases
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsFlockMedicineCardiologyInternal medicineDifferential diagnosisDilated cardiomyopathyElectrocardiographyPulmonary hypertensionDiseaseHeart failurePathologyVeterinary medicine

Abstract

fetched live from OpenAlex

This chapter presents the details about clinical history, causative agent, clinical signs and lesions, transmission route, diagnostic tests, differential diagnosis, and prevention and control of cardiovascular diseases that include dilated cardiomyopathy, pulmonary hypertension syndrome, aortic rupture/dissecting aneurysm, round heart disease, nutritional and toxic cardiopathies, and infectious cardiopathies. There are a number of differences between the avian and the mammalian heart, some of which have clinical implications in the pathophysiology and diagnosis of poultry cardiovascular diseases. Electrocardiography (ECG) is invaluable to investigate conduction disorders and arrhythmia. Common ECG abnormalities in chickens include mean QRS axis deviation, ventricular premature contractions, and atrioventricular blocks. Ascites/pulmonary hypertension syndrome is one of the most common causes of mortality in commercial flocks of broilers, with an average prevalence of approximately 4.7%, which can go as high as 15-20% in certain roaster chicken flocks. Younger poultry birds are more commonly affected by nutritional deficiencies and excess.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.098
Threshold uncertainty score0.329

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0980.039

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 head0.009
GPT teacher head0.238
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2021
Admission routes1
Has abstractyes

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