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Record W2026735688 · doi:10.1034/j.1600-0579.6.s3.5.x

1.3 Development of professional competences

2002· article· en· W2026735688 on OpenAlexaff
Alphons J. M. Plasschaert, Marcia A. Boyd, Sandra C. Andrieu, R M Basker, Roberto J. Beltrán, Giorgio Blasi, Barbara Chadwick, David W. Chambers, Cecilia Christersson, Fernando Haddock, Thomas Kerschbaum, S.L. Kogon, György Kövesi, Füsun Özer, Hari Parkash, Juanita E. Villamil, Richard I. Vogel, Anne Wolowski

Bibliographic record

VenueEuropean Journal Of Dental Education · 2002
Typearticle
Languageen
FieldHealth Professions
TopicDental Education, Practice, Research
Canadian institutionsWestern UniversityUniversity of British Columbia
Fundersnot available
KeywordsCurriculumMedical educationNorm (philosophy)PsychologyHealth careDental educationPolitical scienceMedicinePedagogy

Abstract

fetched live from OpenAlex

Competency-based education, introduced approximately 10 years ago, has become the preferred method and generally the accepted norm for delivering and assessing the outcomes of undergraduate (European) or predoctoral (North America) dental education in many parts of the world. As a philosophical approach, the competency statements drive national agencies in external programme review and at the institutional level in the definition of curriculum development, student assessment and programme evaluation. It would be presumptuous of this group to prescribe competences for various parts of the world; the application of this approach on a global basis may define what is the absolute minimum knowledge base and behavioural standard expected of a 'dentist' in the health care setting, while respecting local limitations and values. The review of documents and distillation of recommendations is presented as a reference and consideration for dental undergraduate programmes and their administration.

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 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)0.008
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.009
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0010.004
Scholarly communication0.0050.002
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0090.005

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 head0.110
GPT teacher head0.470
Teacher spread0.360 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations47
Published2002
Admission routes1
Has abstractyes

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