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Record W4284896960 · doi:10.24875/rmn.m22000087

Neurological complications of interatrial blocks and BayesÓ? syndrome

2022· article· en· W4284896960 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.

Bibliographic record

VenueRevista de Fomento Social · 2022
Typearticle
Languageen
FieldNeuroscience
TopicSpatial Neglect and Hemispheric Dysfunction
Canadian institutionsQueen's University
Fundersnot available
KeywordsBayes' theoremMedicineCardiologyInternal medicineComputer scienceArtificial intelligenceBayesian probability

Abstract

fetched live from OpenAlex

Interatrial blocks (IABs) are a variety of abnormalities in the interatrial conduction. Bayes' syndrome is a clinical entity based on the association between advanced IABs and supraventricular tachyarrhythmias, being atrial fibrillation (AF) the most frequent. Due to its negative effects on left atrial electromechanical function, both IABs and Bayes' syndrome are associated with thromboembolic phenomena, causing cardiovascular and neurological complications. In regard to neurological involvement, patients with these conditions have an increased incidence of ischemic events, cognitive impairment, and dementia. These observations triggered the question whether the use of early anticoagulation therapy (before the documentation of AF) could prevent thromboembolic events in patients with IABs diagnosis. This review aims to summarize the most recent evidence describing the association of IABs and Bayes' syndrome with neurological events. Potential early therapeutic options to prevent these undesirable clinical consequences will be also discussed.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.889
Threshold uncertainty score0.639

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.274
Teacher spread0.247 · 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