Abstracts Presented at the American Urological Association Annual Meeting: Determinants of Subsequent Peer Reviewed Publication
Bibliographic record
Abstract
PURPOSE: Abstracts submitted to medical meetings do not undergo the same critical peer review process as published manuscripts. Despite this limited scrutiny presented abstracts often influence clinical thinking and practice. Consequently the peer reviewed publication rate of abstracts becomes critical in judging the quality of this research. We determined this publication rate and factors influencing it. MATERIALS AND METHODS: All 1,584 abstracts presented at the 2000 American Urological Association Annual Meeting were reviewed and assessed for subsequent publication with a fixed MEDLINE search protocol. We searched for publications from January 1, 1999 to May 31, 2005. Abstracts were deemed published if 1) at least 1 author of the presented abstract was a manuscript author and 2) at least 1 conclusion in the presented abstract was included in the final publication conclusions. Publication rates according to mode and topic of presentation, country or state of origin and time to publication were calculated. Journal impact factors for publications were compared according to these variables. RESULTS: Of presented abstracts from the 2000 American Urological Association meeting 55% went on to successful publication, including 59% of podium, 55% of poster, 55% of unmoderated poster and 42% of video presentations. Mean time from presentation to publication was 17 months. The average journal impact factor was 3.2. CONCLUSIONS: A significant proportion of presentations at the American Urological Association Annual Meeting is never subjected to or fails the critical peer review process. The overall journal impact factor for published manuscripts is modest. Meeting attendees should consider these observations when deciding whether to incorporate the findings of presentations into their clinical practice.
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 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 | 0.164 | 0.073 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
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".