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Record W2793838537 · doi:10.1213/ane.0000000000002826

Summative Objective Structured Clinical Examination Assessment at the End of Anesthesia Residency for Perioperative Ultrasound

2018· article· en· W2793838537 on OpenAlexaff
John Mitchell, Rabia Amir, Mario Montealegre-Gallegos, Feroze Mahmood, Marc Shnider, Azad Mashari, Lu Yeh, Ruma Bose, Vanessa Wong, Philip E. Hess, Yannis Amador, Jelliffe Jeganathan, Stephanie B. Jones, Robina Matyal

Bibliographic record

VenueAnesthesia & Analgesia · 2018
Typearticle
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsMedicineObjective structured clinical examinationSummative assessmentMedical physicsUltrasoundImaging phantomPerioperativeWorkflowGrading (engineering)AnesthesiologyMedical educationRadiologyAnesthesiaFormative assessmentStatistics

Abstract

fetched live from OpenAlex

While standardized examinations and data from simulators and phantom models can assess knowledge and manual skills for ultrasound, an Objective Structured Clinical Examination (OSCE) could assess workflow understanding. We recruited 8 experts to develop an OSCE to assess workflow understanding in perioperative ultrasound. The experts used a binary grading system to score 19 graduating anesthesia residents at 6 stations. Overall average performance was 86.2%, and 3 stations had an acceptable internal reliability (Kuder-Richardson formula 20 coefficient >0.5). After refinement, this OSCE can be combined with standardized examinations and data from simulators and phantom models to assess proficiency in ultrasound.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.235
Threshold uncertainty score0.959

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.039
GPT teacher head0.386
Teacher spread0.347 · 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

Citations18
Published2018
Admission routes1
Has abstractyes

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