MétaCan
Menu
Back to cohort
Record W3130485765 · doi:10.1080/21614083.2021.1883941

Cologne Consensus Conference A Meeting of the International Academy for CPD Accreditation A World Apart: We Are Together

2021· article· en· W3130485765 on OpenAlexaboutno aff
Julie Simper

Bibliographic record

VenueJournal of European CME · 2021
Typearticle
Languageen
FieldMedicine
TopicHealth and Medical Research Impacts
Canadian institutionsnot available
Fundersnot available
KeywordsAccreditationNinthPolitical scienceCoronavirus disease 2019 (COVID-19)Medical educationPandemicContinuing medical educationContinuing educationContinuing professional developmentMedicineLibrary scienceProfessional developmentComputer science

Abstract

fetched live from OpenAlex

The ninth annual Cologne Consensus Conference was held virtually on 10–11 September 2020. The two-day educational event was organised by the International Academy for CPD Accreditation (the Academy), a network of colleagues dedicated to promoting and enhancing continuing professional development (CPD) accreditation systems throughout the world. This year’s conference was hosted by the Accreditation Council for Continuing Medical Education (ACCME) and once again planned in cooperation with the European Cardiology Section Foundation (ECSF) and the Royal College of Physicians and Surgeons of Canada. The conference’s ninth iteration was originally slated to be a live meeting taking place in Chicago, Illinois, USA (home to the ACCME offices), but was moved to a fully online format due to the ongoing COVID-19 pandemic. Appropriately, the programme’s theme was A World Apart: We Are Together and focused on the continued alignment of global accreditation standards and increasing international collaborations. This conference report summarises the meeting content and discussions, including a description and formal adoption of the final Standards for Substantive Equivalency between Continuing Professional Development/Continuing Medical Education (CPD/CME) Accreditation Systems.

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)0.002
metaresearch head score (Gemma)0.044
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.452
Threshold uncertainty score0.964

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.044
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 head0.250
GPT teacher head0.432
Teacher spread0.182 · 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.

Study designNot applicable
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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of European CMESame topicHealth and Medical Research ImpactsFrench-language works237,207