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Record W4390401583 · doi:10.1016/j.jsurg.2023.11.001

Effect of Feedback Modality on Simulated Surgical Skills Learning Using Automated Educational Systems– A Four-Arm Randomized Control Trial

2023· article· en· W4390401583 on OpenAlexafffund
Recai Yilmaz, Ali M. Fazlollahi, Alexander Winkler-Schwartz, Anna Wang, Hafila Hassan Makhani, Ahmad Alsayegh, Mohamad Bakhaidar, Dan Huy Tran, Carlo Santaguida, Rolando F. Del Maestro

Bibliographic record

VenueJournal of surgical education · 2023
Typearticle
Languageen
FieldMedicine
TopicSurgical Simulation and Training
Canadian institutionsMcGill UniversityMcGill University Health CentreMontreal Neurological Institute and Hospital
FundersFonds de Recherche du Québec - SantéNational Research Council CanadaMontreal Neurological Institute and HospitalBrain Tumour Foundation of CanadaRoyal College of Physicians and Surgeons of CanadaMcGill University
KeywordsTask (project management)Randomized controlled trialModality (human–computer interaction)Repetition (rhetorical device)Dreyfus model of skill acquisitionComputer sciencePeer feedbackBaseline (sea)Physical medicine and rehabilitationPsychologyPhysical therapyCognitive psychologyMedicineMedical educationArtificial intelligenceSurgery

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.042

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0040.002
Meta-epidemiology (broad)0.0080.003
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0020.002
Open science0.0020.001
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0120.002

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 head0.025
GPT teacher head0.374
Teacher spread0.349 · 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 designRandomized trial
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
Published2023
Admission routes2
Has abstractno

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