Use of Social Media at Cardiovascular Congresses: Opportunities for Education and Dissemination
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.
Bibliographic record
Abstract
Social Media includes different forms of online communication from Twitter, Facebook, Instagram, LinkedIn, podcasts, YouTube etc. and has advanced how information is exchanged. A notable use is engaging on Twitter at medical conferences, both for those attending the conference and the global audience who are not able to attend. It is also increasingly used as an educational tool similar to e-learning. The objective of this paper is to: 1) highlight the impact of using Twitter at cardiovascular congresses as an interactive platform for active learning as compared to passively listening to a presentation; 2) present perspectives from not only clinicians, researchers but also patients on how this information is interpreted; 3) provide recommendations for conference organizers for best practice live tweeting to share the information and knowledge beyond those in attendance; with potential for not only engagement but also educating our global community.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it