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Record W4206992372 · doi:10.29173/cjen146

The Impact of COVID-19 on the Cardiovascular System

2022· article· en· W4206992372 on OpenAlex
Mohamed Toufic El Hussein, Aditi Sharma

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian Journal of Emergency Nursing · 2022
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 Clinical Research Studies
Canadian institutionsRockyview General HospitalMount Royal University
Fundersnot available
KeywordsMedicineDamagesIntensive care medicineSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Severe acute respiratory syndromeCoronavirus disease 2019 (COVID-19)DiseaseCoronavirusEmergency departmentAngiotensin-converting enzyme 2Mechanical ventilationInfectious disease (medical specialty)Emergency medicineMedical emergencyInternal medicineNursing

Abstract

fetched live from OpenAlex

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an infectious disease where symptoms can be mild, requiring no treatment or severe, requiring hospital admission for hemodynamic support and mechanical ventilation. Given the affinity of SARS-CoV-2 to angiotensin-converting enzyme 2 (ACE2) receptors, the heart is a highly susceptible target to its associated damages. Knowledge about SARS-CoV-2 modes of transmission and their impact on the cardiovascular system is paramount for emergency department (ED) nurses to protect themselves and competently care for their patients. The authors of this manuscript aim to provide a clinical overview of the impact of SARS-CoV-2 on the cardiovascular system based on the latest scientific evidence. A profound understanding of SARS-CoV-2 and its related consequences has the potential to minimize its associated mortality and morbidity.

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)0.004
metaresearch head score (Gemma)0.018
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.212
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.101
GPT teacher head0.434
Teacher spread0.333 · 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