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Record W3015826819 · doi:10.1016/j.cjca.2020.04.003

Guidance on Minimizing Risk of Drug-Induced Ventricular Arrhythmia During Treatment of COVID-19: A Statement from the Canadian Heart Rhythm Society

2020· article· en· W3015826819 on OpenAlexaffvenueabout
John L. Sapp, Wael Alqarawi, Ciorsti MacIntyre, Rafik Tadros, Christian Steinberg, Jason D. Roberts, Zachary Laksman, Jeff S. Healey, Andrew D. Krahn

Bibliographic record

VenueCanadian Journal of Cardiology · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsMcMaster UniversityUniversity of British ColumbiaWestern UniversityInstitut universitaire de cardiologie et de pneumologie de QuébecMontreal Heart InstituteUniversity of OttawaDalhousie UniversityPopulation Health Research InstituteUniversité LavalQueen Elizabeth II Health Sciences Centre
FundersBiosense WebsterMedtronicAbbott Laboratories
KeywordsMedicineQT intervalProarrhythmiaTorsades de pointesIntensive care medicineHydroxychloroquineInternal medicineCardiologyCoronavirus disease 2019 (COVID-19)

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.032
metaresearch head score (Gemma)0.107
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.892
Threshold uncertainty score0.214

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0320.107
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0030.002
Science and technology studies0.0030.004
Scholarly communication0.0060.003
Open science0.0080.003
Research integrity0.0350.025
Insufficient payload (model declined to judge)0.0070.006

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 head0.061
GPT teacher head0.357
Teacher spread0.296 · 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
GenreCommentary

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

Citations122
Published2020
Admission routes3
Has abstractno

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