MP66-08 PUBLISHING ETHICS AT MAJOR UROLOGY CONFERENCES: A 14-YEAR ANALYSIS OF ABSTRACT PRESENTATIONS FROM AN AUA SECTIONAL MEETING
Bibliographic record
Abstract
You have accessJournal of UrologyCME1 Apr 2023MP66-08 PUBLISHING ETHICS AT MAJOR UROLOGY CONFERENCES: A 14-YEAR ANALYSIS OF ABSTRACT PRESENTATIONS FROM AN AUA SECTIONAL MEETING Suraj Pursnani, Jacob Feiertag, Zachary Corey, Ahmad Alzubaidi, Erik B. Lehman, and Jay D. Raman Suraj PursnaniSuraj Pursnani More articles by this author , Jacob FeiertagJacob Feiertag More articles by this author , Zachary CoreyZachary Corey More articles by this author , Ahmad AlzubaidiAhmad Alzubaidi More articles by this author , Erik B. LehmanErik B. Lehman More articles by this author , and Jay D. RamanJay D. Raman More articles by this author View All Author Informationhttps://doi.org/10.1097/JU.0000000000003329.08AboutPDF ToolsAdd to favoritesDownload CitationsTrack CitationsPermissionsReprints ShareFacebookLinked InTwitterEmail Abstract INTRODUCTION AND OBJECTIVE: Academic conferences are excellent opportunities to showcase innovative research. However, the same abstract may be submitted to multiple conferences or contain previously published material. This violates exclusive submission criteria of most medical meetings. Duplicate publications account for over 15% of scholarly article retractionswith that number increasing in recent years. This study aimed to investigate the publication ethics of abstracts presented at a sectional American Urological Association (AUA) conference. METHODS: Mid-Atlantic AUA (MA-AUA) abstract submissions from 2008 to 2021 were collected from the Canadian Journal of Urology website. Abstract titles and authors were searched in a standard fashion using PubMed, Google Scholar, and Google. Characteristic data was collected, including manuscript publication date and journal of publication. RESULTS: Over the study interval, 1372 abstracts were presented. Of these, 466 (34.0%) were published as manuscripts while 906 (66.0%) did not get published. Of the published manuscripts, 59 (12.7%) were published prior to the conference date. The mean time of publication prior to the conference was 5±4.8 months (range, 1–31 months; Figure 1). Of the 906 presented abstracts that were not published as manuscripts, 102 (11.3%) were submitted as abstracts to other academic meetings either before or after the MA-AUA conference. Categories with the most manuscripts published prior to the meeting included prostate cancer, kidney cancer, and general trends and socioeconomics. CONCLUSIONS: Most research presented at an AUA sectional meeting over the past 14 years was novel and abided by standard publication practices. However, double abstract submissions (11%) and previously published manuscript data (13%) remain an issue within urologic academia. Peer reviewers for academic conferences cannot be expected to know if an abstract had already been published or presented. Submitting authors should abide by ethical submission practices. Source of Funding: None © 2023 by American Urological Association Education and Research, Inc.FiguresReferencesRelatedDetails Volume 209Issue Supplement 4April 2023Page: e934 Advertisement Copyright & Permissions© 2023 by American Urological Association Education and Research, Inc.MetricsAuthor Information Suraj Pursnani More articles by this author Jacob Feiertag More articles by this author Zachary Corey More articles by this author Ahmad Alzubaidi More articles by this author Erik B. Lehman More articles by this author Jay D. Raman More articles by this author Expand All Advertisement PDF downloadLoading ...
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 | 0.029 | 0.143 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.020 | 0.006 |
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".