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Record W3090085971 · doi:10.1177/0253717620957524

The Relevance of Telemedicine in Continuing Medical Education

2020· article· en· W3090085971 on OpenAlex

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

VenueIndian Journal of Psychological Medicine · 2020
Typearticle
Languageen
FieldMedicine
TopicInnovations in Medical Education
Canadian institutionsSt. Thomas Hospital
Fundersnot available
KeywordsInteractivityRelevance (law)Flexibility (engineering)Continuing medical educationBridge (graph theory)Medical educationContinuing educationTelemedicineComputer scienceKnowledge managementPsychologyEngineering ethicsMultimediaMedicineHealth careEngineeringPolitical scienceManagement

Abstract

fetched live from OpenAlex

Continuing medical education (CME) is essential for medical practitioners to update their knowledge and skills periodically to provide clinical care in keeping with the evidence available. Traditional methods of CME such as workshops, conferences, and seminars are helpful to bridge the gaps in practice. With advancing technologies, online format is used to deliver CME with appropriate modifications. Although there are distinct advantages of online CME in regards to wider reach and flexibility, there are certain drawbacks beyond just technological limitations. Interactivity using ingenious ideas may be required to motivate and engage learners during online CME.

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)0.003
metaresearch head score (Gemma)0.042
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.903
Threshold uncertainty score0.966

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.042
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.403
Teacher spread0.374 · 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