MétaCan
Menu
Back to cohort
Record W2333390882 · doi:10.1503/cmaj.141417

Advancing social media in medical education

2015· article· en· W2333390882 on OpenAlexaffvenueabout
Wendy Davis, Kendall Ho, Jason Last

Bibliographic record

VenueCanadian Medical Association Journal · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Media in Health Education
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGrassrootsSocial mediaValue (mathematics)Public relationsMedical educationComputer scienceMedicinePolitical scienceWorld Wide WebLawPolitics

Abstract

fetched live from OpenAlex

See also page [547][1] and [www.cmaj.ca/lookup/doi/10.1503/cmaj.150248][2] With rapid, grassroots adoption of social media in medical education, concerns are emerging about potential risks, while benefits may be unclear. Social media holds great value as a teaching and learning tool. Canadian

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)0.016
metaresearch head score (Gemma)0.036
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: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.098
Threshold uncertainty score0.328

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.036
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.002
Science and technology studies0.0040.005
Scholarly communication0.0080.010
Open science0.0020.008
Research integrity0.0080.007
Insufficient payload (model declined to judge)0.0980.020

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 head0.042
GPT teacher head0.384
Teacher spread0.341 · 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
GenreCommentary

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

Citations66
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Medical Association JournalSame topicSocial Media in Health EducationFrench-language works237,207