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Record W4243770048 · doi:10.3109/21614083.2013.812965

State of play of CME in Europe in 2012: proceedings from the fifth annual meeting of the European CME Forum

2013· article· en· W4243770048 on OpenAlexaboutno aff
Eugene Pozniak, Ryan Woodrow, Philippa Flemming

Bibliographic record

VenueJournal of European CME · 2013
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationPanel discussionPolitical scienceSession (web analytics)Medical educationContinuing medical educationWork (physics)State (computer science)Library sciencePublic relationsMedicineContinuing educationEngineeringBusiness

Abstract

fetched live from OpenAlex

One hundred and thirty speakers and delegates met in London for the fifth annual meeting of the European CME Forum which took place on 15 and 16 November 2012. Over the two days, current and future trends in European Continuing Medical Education (CME) were examined, discussed and debated. The meeting employed a mixture of styles: plenary presentations, workshops and panel discussion, but with a high focus on open question-and-answer interaction between speakers and delegates.The predominant target audience comprised people with an interest in European CME including the accreditation bodies, scientific societies, education providers, medical communications agencies and industry supporters.Each interest group had a dedicated meeting on the day before the formal programme; European pharmaceutical company involvement, scientific societies and the Good CME Practice Group which announced that following the publication of its recent work, it was opening its membership to all qualifying providers. A pre-meeting needs assessment was carried out which informed the programme structure and led to a more interactive format.Session themes included the new European Accreditation Council for CME (EACCME) accreditation criteria, e-learning, panel discussions with experts from throughout Europe as well as CME professionals from the USA, Canada, India and Australia.

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 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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.457
Threshold uncertainty score0.457

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.011
GPT teacher head0.258
Teacher spread0.247 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations0
Published2013
Admission routes1
Has abstractyes

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