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Record W3169176333 · doi:10.1016/j.cjco.2021.05.015

An Evaluation of Cardiology Virtual Care During the COVID-19 Pandemic

2021· article· en· W3169176333 on OpenAlexaff
Kate E. Sanderson, Karen Spithoff, Marija Corovic, Kara M. Langdon, Jon-David Schwalm

Bibliographic record

VenueCJC Open · 2021
Typearticle
Languageen
FieldMedicine
TopicTelemedicine and Telehealth Implementation
Canadian institutionsHamilton Health SciencesPopulation Health Research InstituteMcMaster UniversityHealth Sciences Centre
Fundersnot available
KeywordsPandemicCoronavirus disease 2019 (COVID-19)Health careMedicineTelemedicine2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Medical emergencyFamily medicineInternal medicineDiseaseVirology

Abstract

fetched live from OpenAlex

A survey evaluation was conducted in the division of cardiology at a tertiary care academic centre to assess barriers, facilitators, acceptability, and feasibility of virtual care during the COVID-19 pandemic. Survey responses from 26 health care providers, 45 patients, and 2 caregivers showed that virtual visits (primarily by telephone) were feasible and generally acceptable to most respondents. Key opportunities for improvement included availability of easy-to-use video platforms, space and equipment in clinics, provision of information to patients before visits, and appropriate selection of patients for virtual visits. Results will inform optimization of virtual care during this pandemic and beyond.

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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.486

Codex and Gemma teacher scores by category

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

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 head0.151
GPT teacher head0.479
Teacher spread0.328 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations11
Published2021
Admission routes1
Has abstractyes

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