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Record W4200598254 · doi:10.1503/cmaj.210831

Prevention and management of hyperkalemia in patients treated with renin–angiotensin–aldosterone system inhibitors

2021· review· en· W4200598254 on OpenAlexaffvenue
Jordan Weinstein, Louis Girard, Serge Lepage, Robert S. McKelvie, Karthik Tennankore

Bibliographic record

VenueCanadian Medical Association Journal · 2021
Typereview
Languageen
FieldMedicine
TopicPotassium and Related Disorders
Canadian institutionsNova Scotia Health AuthorityCégep de SherbrookeSt Joseph's Health CareDalhousie UniversityUniversity of CalgaryUniversité de SherbrookeSt. Michael's HospitalWestern University
Fundersnot available
KeywordsHyperkalemiaAldosteroneRenin–angiotensin systemMedicinePotassiumInternal medicineEndocrinologyCardiologyPharmacologyChemistryBlood pressure

Abstract

fetched live from OpenAlex

KEY POINTS Hyperkalemia, defined as a serum potassium level of 5.0 mmol/L or greater, can lead to severe electrophysiological disturbances, including cardiac arrythmias, that increase morbidity and risk of death.[1][1] It is common in patients with conditions that impair potassium excretion by the

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.001

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 head0.008
GPT teacher head0.240
Teacher spread0.232 · 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 designSystematic review
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

Citations32
Published2021
Admission routes2
Has abstractyes

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