MétaCan
Menu
Back to cohort
Record W2321943053 · doi:10.1097/eja.0000000000000133

Reply to

2014· letter· en· W2321943053 on OpenAlexaboutno aff
Karin Graeser, Lars Konge

Bibliographic record

VenueEuropean Journal of Anaesthesiology · 2014
Typeletter
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsnot available
Fundersnot available
KeywordsVirtual realityMedicineCompetence (human resources)RealismTask (project management)PerceptionFidelityMedical educationHuman–computer interactionPsychologyComputer scienceVisual artsSocial psychology

Abstract

fetched live from OpenAlex

Editor, We thank Dr Badiger et al.1 for their interest in our article.2 Since our first study on the prototype,3 we have followed the development of the ORSIM virtual reality bronchoscopy simulator (Airway Simulation Limited, Auckland, New Zealand) and are pleased that the experiences of Dr Badiger et al. are positive with the commercially available version. Interestingly, their findings closely resemble earlier results published on the other virtual-reality simulator in our study (AccuTouch; CAE Healthcare, Montreal, Canada).4 However, it is important to acknowledge that neither trainees’ self-assessed learning gain nor their perception of simulation realism are valid measures of the efficacy of the training. Literature shows that we cannot trust self-assessment5 and the fact that trainees feel more confident after a training intervention should not be equalled to increased competence. The importance of realism in simulation is under debate and a recent review found only a minimal relationship between simulation fidelity and transfer of learning.6 Virtual-reality simulators can show a range of difficult airway scenarios, but only the most expensive ones provide haptic feedback. Tube advancement is a key component of fibreoptic intubation and can only be practised on physical models. No evidence favours virtual-reality simulation over practising on mannequins when learning fibreoptic intubation. The best possible way of practising the procedure remains to be established. In a recent randomised controlled study,7 we compared part-task training with whole-task training and found a positive learning effect in both groups but no significant differences in fibreoptic intubation skills between groups. Future studies should compare different approaches to training and ideally use blinded assessments of real procedures as outcome measures (transfer studies). In conclusion, we agree that fibreoptic intubation should be practised in a simulated environment prior to performance on patients. Available, local resources should decide which teaching modalities to use. Acknowledgements relating to this article Assistance with the letter: none. Financial support and sponsorship: none. Conflicts of interest: none.

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)0.004
metaresearch head score (Gemma)0.055
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.956
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.055
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.003
Scholarly communication0.0040.006
Open science0.0030.003
Research integrity0.0180.025
Insufficient payload (model declined to judge)0.0440.035

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 head0.050
GPT teacher head0.322
Teacher spread0.272 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations1
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of AnaesthesiologySame topicSimulation-Based Education in HealthcareFrench-language works237,207