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Record W3023363672 · doi:10.1177/0846537120924310

The Canadian Association for Interventional Radiology (CAIR) and Canadian Association of Radiologists (CAR) Guidelines for Interventional Radiology Procedures for Patients With Suspected or Confirmed COVID-19

2020· article· en· W3023363672 on OpenAlexaffabout
Amol Mujoomdar, Tara Graham, Mark O. Baerlocher, Gilles Soulez

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicCOVID-19 and healthcare impacts
Canadian institutionsUniversité de MontréalRoyal Victoria HospitalVictoria HospitalTrillium Health CentreLondon Health Sciences Centre
Fundersnot available
KeywordsMedicineInterventional radiologyCoronavirus disease 2019 (COVID-19)PandemicPersonal protective equipmentRadiologyHealth carePatient careMedical physicsSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Medical emergencyDiseaseNursingPathologyInfectious disease (medical specialty)

Abstract

fetched live from OpenAlex

The current coronavirus disease 2019 (COVID-19) pandemic is creating significant challenges to the Canadian health system, including the practice of interventional radiology (IR). Interventional radiology will continue to play an important role in patient care, during this crisis. This document serves to guide interventional and general radiologists in safely performing IR procedures on patients with suspected or confirmed COVID-19, using the best evidence, guidelines and expert recommendations available. These strategies include reviewing procedural indications, development of tactics to minimize cross contamination prior to the intervention, appropriate usage of personal protection equipment according to the type of procedure (along with defining aerosol-generating procedures in IR), along with developing the appropriate work environment during the COVID-19 pandemic. By adopting the policies described, hospitals will protect the interventional radiologists, medical radiation technologists, nurses, ancillary staff, along with patients who benefit from their care.

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)0.005
metaresearch head score (Gemma)0.123
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.694
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.123
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.083
GPT teacher head0.381
Teacher spread0.298 · 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.

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

Citations14
Published2020
Admission routes2
Has abstractyes

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