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Record W4206902600 · doi:10.7759/cureus.21594

The PHOENIX: Design and Development of a Three-Dimensional-Printed Drone Prototype and Corresponding Simulation Scenario Based on the Management of Cardiac Arrest

2022· article· en· W4206902600 on OpenAlexaff
Bruno Gino, Kerry-Lynn Williams, Claire Siobhan Neilson, Philip d'Entremont, Adam Dubrowski, Tia Renouf

Bibliographic record

VenueCureus · 2022
Typearticle
Languageen
FieldMedicine
TopicCardiac Arrest and Resuscitation
Canadian institutionsMemorial University of NewfoundlandUniversity of Ontario Institute of Technology
Fundersnot available
KeywordsMedicineSudden cardiac arrestDefibrillationVentricular fibrillationStandardizationMedical emergencyCardiopulmonary resuscitationIntervention (counseling)Health careDroneVentricular tachycardiaHealth professionalsChain of survivalIntensive care medicineResuscitationBasic life supportNursingCardiologyEmergency medicineComputer science

Abstract

fetched live from OpenAlex

Sudden cardiac arrest (SCA) remains one of the most prevalent cardiovascular emergencies in the world. The development of international protocols and the use of accessible devices such as automated external defibrillators (AEDs) allowed for the standardization and organization of medical care related to SCA. When defibrillation is performed within five minutes of starting ventricular fibrillation (VF) and pulseless ventricular tachycardia (VT), the victim survival rate has increased considerably. Therefore, training healthcare professionals to use AEDs correctly is essential to improve patient outcomes and response time in the intervention. In this technical report, we advocate simulation-based education as a teaching methodology and an essential component of drone adaptation, novel technology, that can deliver AEDs to the site, as well as a training scenario to teach healthcare professionals how to operate the real-time communication components of drones and AEDs efficiently. Studies have suggested that simulation can be an effective way to train healthcare professionals. Through teaching methodology using simulation, training these audiences has the potential to reduce the response time to intervention, consequently, increasing the patient's chance of surviving.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.492
Threshold uncertainty score0.225

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 head0.030
GPT teacher head0.272
Teacher spread0.242 · 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 designSimulation or modeling
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

Citations7
Published2022
Admission routes1
Has abstractyes

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