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Record W3031914512 · doi:10.1016/j.cjca.2020.05.033

Use of Renin-Angiotensin System Blockers During the COVID-19 Pandemic: Early Guidance and Evolving Evidence

2020· article· en· W3031914512 on OpenAlexaffvenue
Ricky D. Turgeon, Shelley Zieroth, David Bewick, Chi-Ming Chow, Brian Clarke, Simone Cowan, Christopher B. Fordyce, Anne Fournier, Kenneth Gin, Anil Gupta, Sean Hardiman, Simon Jackson, Benny Lau, Howard Leong‐Poi, Samer Mansour, Ariane Marelli, Ata Rehman Quraishi, Idan Roifman, Marc Ruel, John L. Sapp, Gurmeet Singh, Gary R. Small, Sean Virani, David Wood, Andrew D. Krahn

Bibliographic record

VenueCanadian Journal of Cardiology · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsUniversity of OttawaMcGill UniversityCentre Hospitalier de l’Université de MontréalQueen Elizabeth II Health Sciences CentreUniversity of AlbertaProvincial Health Services AuthorityUniversity of ManitobaTrillium Health CentreUniversité de MontréalDalhousie UniversityCentre Hospitalier Universitaire Sainte-JustineHealth Sciences CentreLibin Cardiovascular Institute of AlbertaUniversity of TorontoUniversity of CalgarySunnybrook Health Science CentreSt. Michael's HospitalUniversity of British Columbia
FundersServierEdwards LifesciencesNovartis
KeywordsMedicineHeart failurePandemicAngiotensin Receptor BlockersHarmCoronavirus disease 2019 (COVID-19)Internal medicineIntensive care medicineCardiologyRenin–angiotensin systemDiseaseBlood pressure

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)0.030
metaresearch head score (Gemma)0.174
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.056
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0300.174
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.004
Bibliometrics0.0020.004
Science and technology studies0.0010.002
Scholarly communication0.0080.005
Open science0.0040.002
Research integrity0.0100.014
Insufficient payload (model declined to judge)0.0060.001

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 head0.163
GPT teacher head0.378
Teacher spread0.215 · 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

Citations3
Published2020
Admission routes2
Has abstractno

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