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Record W2133780453 · doi:10.1177/1553350606291042

A Novel Method of Assessing Clinical Reasoning in Surgical Residents

2006· review· en· W2133780453 on OpenAlex
Sarkis Meterissian

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

VenueSurgical Innovation · 2006
Typereview
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMcGill UniversityMontreal General Hospital
Fundersnot available
KeywordsSummative assessmentConcordanceFormative assessmentMedicineTest (biology)Medical educationClinical judgmentMedical physicsPsychologyMathematics education

Abstract

fetched live from OpenAlex

At present, surgical educators can readily assess knowledge with multiple-choice examinations, and inanimate models can be used to assess technical skills. Clinical judgment and reasoning are indispensable skills used by expert surgeons to solve ill-defined problems encountered in the emergency department, clinic, and operating room. The Script Concordance Test, a new tool of clinical reasoning assessment, can test the elaborated networks of knowledge that experienced surgeons develop over the years. It allows for multiple different approaches to the same problem and could be developed as both a formative and summative assessment tool in general surgery residency programs. This article explores the theoretical and practical aspects of the Script Concordance Test.

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)0.007
metaresearch head score (Gemma)0.043
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.987
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.043
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.004
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.002
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 head0.195
GPT teacher head0.543
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