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Record W2795935625 · doi:10.1007/s43678-021-00167-y

2021 CAEP Acute Atrial Fibrillation/Flutter Best Practices Checklist

2021· review· en· W2795935625 on OpenAlexaff
Ian G. Stiell, Kerstin de Wit, Frank Scheuermeyer, Alain Vadeboncœur, Paul Angaran, Debra Eagles, Ian D. Graham, Clare Atzema, Patrick Archambault, Troy Tebbenham, Andrew D. McRae, Warren J. Cheung, Ratika Parkash, Marc W. Deyell, Geneviève Baril, Rick Mann, Rupinder Sahsi, Suneel Upadhye, Erica Brown, Jennifer Brinkhurst, Christian Chabot, Allan C. Skanes

Bibliographic record

VenueCanadian Journal of Emergency Medicine · 2021
Typereview
Languageen
FieldMedicine
TopicAtrial Fibrillation Management and Outcomes
Canadian institutionsUniversité du QuébecTrillium Health CentreSt Mary's Hospital CentreCégep de SherbrookeDalhousie UniversityUniversity of CalgaryUniversity of OttawaInstitute for Clinical Evaluative SciencesWestern UniversityUniversity of TorontoSt. Michael's HospitalUniversité LavalUniversité de MontréalQueen's UniversityMcMaster UniversityUniversity of British ColumbiaMontreal Heart InstituteOttawa Hospital
Fundersnot available
KeywordsMedicineChecklistAtrial fibrillationAtrial flutterFlutterCardiologyInternal medicinePsychology

Abstract

fetched live from OpenAlex

A. Assessment and risk stratification Is AF/AFL with rapid ventricular response a primary arrhythmia or secondary to medical causes?A. Rapid rate secondary to medical causes (usually in patients with pre-existing/permanent AF) e.g., sepsis, bleeding, PE, heart failure, ACS, etc.:• Investigate and treat underlying causes aggressively • Cardioversion may be harmful • Avoid aggressive rate control B.

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)0.003
metaresearch head score (Gemma)0.016
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: Not applicable
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.038
Threshold uncertainty score0.128

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.016
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.003
Bibliometrics0.0090.006
Science and technology studies0.0010.000
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0380.011

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 head0.310
GPT teacher head0.475
Teacher spread0.165 · 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
GenreReview

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

Citations61
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Emergency MedicineSame topicAtrial Fibrillation Management and OutcomesFrench-language works237,207