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Record W3123716856 · doi:10.1111/eje.12649

Script concordance tests: A call for action in dental education

2021· article· en· W3123716856 on OpenAlex
Sibylle Vital, Claudine Wulfman, Félix Girard, Faleh Tamimi, Bernard Charlin, Maxime Ducret

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

VenueEuropean Journal Of Dental Education · 2021
Typearticle
Languageen
FieldMedicine
TopicClinical Reasoning and Diagnostic Skills
Canadian institutionsMcGill UniversityUniversité de Montréal
Fundersnot available
KeywordsConcordanceTest (biology)Dental educationMedical educationPsychologyClinical judgmentAction (physics)MedicineMedical physics

Abstract

fetched live from OpenAlex

The Script Concordance Test (SCT) is an educational tool that aims to assess the ability to interpret medical information under conditions of uncertainty. It is widely used and validated in health education, but almost unknown in dentistry. Based on authentic clinical problem-solving situations, it allows to assess clinical reasoning that experienced health workers develop over the years. A specific scoring system, dedicated to SCT, considers the variability of responses of practitioners in the same clinical situations. Finally, the scores generated by SCT reflect the respondents' ability to interpret clinical data compared to experienced clinicians. This article aims to familiarise the dental educators' community with SCT construction, optimisation and its possible applications.

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)0.000
metaresearch head score (Gemma)0.013
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.034
GPT teacher head0.379
Teacher spread0.345 · 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