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Record W2127611201 · doi:10.1093/europace/eup328

Animal models for atrial fibrillation: clinical insights and scientific opportunities

2009· review· en· W2127611201 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEP Europace · 2009
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversité de MontréalMontreal Heart Institute
FundersCanadian Institutes of Health Research
KeywordsMedicineAtrial fibrillationAnimal modelClinical PracticeIntensive care medicineNeuroscienceCardiologyInternal medicine

Abstract

fetched live from OpenAlex

Atrial fibrillation (AF) is the most common arrhythmia in clinical practice. A variety of animal models have been used to study the pathophysiology of AF, including molecular basis, ion-current determinants, anatomical features, and macroscopic mechanisms. In addition, animal models play a key role in the development of new therapeutic approaches, whether drug-based, molecular therapeutics, or device-related. This article discusses the various types of animal models that have been used for AF research, reviews the principle mechanisms governing atrial arrhythmias in each model, and provides some guidelines for model selection for various purposes.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
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 head0.468
GPT teacher head0.462
Teacher spread0.006 · 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