American Heart Association EPI|Lifestyle Scientific Sessions: 2021 Meeting Highlights
Bibliographic record
Abstract
he annual American Heart Association (AHA) EPI|Lifestyle Scientific Sessions for 2021 was held in a virtual format from May 20 to 21, 2021.The AHA EPI|Lifestyle Scientific Sessions were combined meetings of the Council on Epidemiology and Prevention (EPI) and the Council on Lifestyle and Cardiometabolic Health.The 2021 conference's theme was Health Equity and Social Justice and highlighted keynote sessions on health equity, structural racism, and COVID-19 and cardiovascular disease (CVD) research.Results from observational studies and randomized controlled trials were presented at the meeting, including research on topics such as social determinants of health, maternal and child health, omics, nutrition, physical activity, and sleep.Participants of the virtual conference included clinicians, public health professionals, and trainees.Over 600 people took part in this year's event, which hosted 212 poster presentations, 66 moderated posters, and 80 oral presentations.The meeting chair representing the Council on Lifestyle and Cardiometabolic Health was Dr Kristie Lancaster from New York University, and Dr Pamela Lutsey from the University of Minnesota represented the EPI council.The vice chairs were Dr Marie-France Hivert from
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.227 | 0.128 |
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".