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Management of Simulated Oxygen Supply Failure: Is There a Gap in the Curriculum?

2006· article· en· W1984594408 on OpenAlexaff
Peta G Lorraway, Georges L. Savoldelli, Hwan S. Joo, Deven Chandra, Roger Chow, Viren N. Naik

Bibliographic record

VenueAnesthesia & Analgesia · 2006
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsUniversity of TorontoSt. Michael's HospitalThe Wilson Centre
Fundersnot available
KeywordsMedicineDelegationPerioperativeCurriculumOxygenPerioperative nursingMedical educationOperations managementMedical emergencyAnesthesiaManagementPsychology

Abstract

fetched live from OpenAlex

In Brief In this study we evaluated, in our residency program, the understanding and management of a simulated oxygen pipeline failure. Performances of 20 residents were evaluated by 2 raters. Fourth-year residents did not perform better than second-year residents (P = NS). The majority of the participants either did not have the knowledge to change the oxygen cylinder or did not attempt to change the oxygen, even after prompting. We conclude that the delegation of gas machine maintenance to perioperative personnel, such as respiratory therapists and technicians, may have created a new gap in knowledge and resulted in inadequate training. IMPLICATIONS: Residents showed deficiency in managing simulated oxygen failure. The majority of the participants did not recognize the problem and did not know how to change the oxygen cylinder. The delegation of gas machine maintenance to perioperative personnel may have created this new gap in equipment knowledge.

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)0.005
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.017
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.296
Teacher spread0.280 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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

Citations28
Published2006
Admission routes1
Has abstractyes

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