Publication rate of abstracts presented at the annual meeting of the American Urological Association
Bibliographic record
Abstract
OBJECTIVE: To determine the rate and time-course of peer-reviewed publication of abstracts presented at the annual meetings of the American Urological Association (AUA). METHODS: All abstracts presented at the annual meetings of the AUA from 1998 to 2000 were searched in the PubMed database. To assess any significant predictors of ultimate peer-reviewed publication, abstract number, meeting year, presentation type (podium vs poster), type of research (basic vs clinical), date of publication and session name (i.e. prostate cancer: advanced) were entered into a database. RESULTS: The overall rate of publication was 37.8%. Survival analysis indicated that most abstracts were published within 2 years of their respective meetings. Univariate and multivariate techniques showed that none of the tested covariates were significant predictors of publication. CONCLUSIONS: Information presented at the AUA annual meetings should be carefully considered by physicians before implementation into their clinical practice. Researchers are encouraged to publish their data.
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 | 0.079 | 0.324 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.024 | 0.019 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".