Poster presentations at medical conferences: an effective way of disseminating research?
Bibliographic record
Abstract
This study aimed to ascertain the value of posters at medical meetings to presenters and delegates. The usefulness of posters to presenters at national and international meetings was evaluated by assessing the numbers of delegates visiting them and the reasons why they visited. Memorability of selected posters was assessed and factors influencing their appeal to expert delegates identified. At both the national and international meetings, very few delegates (< 5%) visited posters. Only a minority read them and fewer asked useful questions. Recall of content was so poor that it prevented identification of factors improving their memorability. Factors increasing posters' visual appeal included their scientific content, pictures/graphs and limited use of words. Few delegates visit posters and those doing so recall little of their content. To engage their audience, researchers should design visually appealing posters by presenting high quality data in pictures or graphs without an excess of words.
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 | 0.180 | 0.363 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.009 | 0.006 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.028 | 0.029 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.016 | 0.019 |
| Insufficient payload (model declined to judge) | 0.148 | 0.040 |
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".