MétaCan
Menu
Back to cohort
Record W6888917311 · doi:10.24433/co.9857122.v1

The Inverse Problem for Cardiac Arrhythmias

2023· other· en· W6888917311 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

VenueCode Ocean · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsMcGill University
Fundersnot available
KeywordsAbnormalityRisk stratificationInverse problemCardiac arrhythmiaAmbulatoryAmbulatory ECGMechanism (biology)

Abstract

fetched live from OpenAlex

A cardiac arrhythmia is an abnormality in the rate or rhythm of the heart beat. We study a type of arrhythmia called a premature ventricular complex (PVC), which is typically benign, but in rare cases can lead to more serious arrhythmias or heart failure. There are three known mechanisms for PVCs: reentry, an ectopic focus, and triggered activity. We develop minimal models for each mechanism and attempt the inverse problem of determining which model (and therefore which mechanism) best describes the beat dynamics observed in an ambulatory electrocardiogram. We demonstrate our approach on a patient who exhibits frequent PVCs and find that their PVC dynamics are best described by a model of triggered activity. Better identification of PVC mechanism from wearable device data could improve risk stratification for the development of more serious arrhythmias.

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), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.018
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0000.018

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 head0.026
GPT teacher head0.270
Teacher spread0.244 · 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

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueCode OceanFrench-language works237,207