MétaCan
Menu
Back to cohort
Record W2473633569 · doi:10.1097/sih.0000000000000172

An Approach to Confederate Training Within the Context of Simulation-Based Research

2016· article· en· W2473633569 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSimulation in Healthcare The Journal of the Society for Simulation in Healthcare · 2016
Typearticle
Languageen
FieldMedicine
TopicSimulation-Based Education in Healthcare
Canadian institutionsMontreal Children's HospitalCanadian Foundation for Healthcare ImprovementUniversity of CalgaryMcGill UniversityRoyal College of Physicians and Surgeons of CanadaAlberta Children's Hospital
Fundersnot available
KeywordsContext (archaeology)Outcome (game theory)ScholarshipProcess (computing)Statement (logic)Computer scienceTraining (meteorology)PsychologyPolitical science

Abstract

fetched live from OpenAlex

STATEMENT: Simulation-based education often relies on confederates, who provide information or perform clinical tasks during simulation scenarios, to play roles. Although there is experience with confederates in their more routine performance within educational programs, there is little literature on the training of confederates in the context of simulation-based research. The CPR CARES multicenter research study design included 2 confederate roles, in which confederates' behavior was tightly scripted to avoid confounding primary outcome measures. In this report, we describe our training process, our method of adherence assessment, and suggest next steps regarding confederate training scholarship.

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.

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)0.014
metaresearch head score (Gemma)0.004
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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score0.934

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0140.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.259
GPT teacher head0.482
Teacher spread0.223 · 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