Frequency and factors influencing publication of abstracts presented at three major nephrology meetings
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: There have been no contemporary studies assessing abstract publication rates and the factors associated with full publication within the field of nephrology. As such, it is unclear whether a publication bias exists for abstracts presented at nephrology meetings, which may hinder the dissemination of potentially important results. Our objective was to review a selection of abstracts presented at 3 major nephrology meetings to determine the proportion that reach full publication and factors associated with full publication. METHODS: 300 randomly selected abstracts presented as posters at three annual nephrology meetings in 2006 [American Society of Nephrology (ASN), European Renal Association (ERA), and National Kidney Foundation (NKF)] were reviewed. Accepted methods of literature search were performed to determine subsequent journal publication. Univariate and multivariate analyses were performed to determine the association between abstract characteristics and subsequent full publication. RESULTS: 127 (42%) abstracts were published in peer-reviewed journals at 4.5 years. On multivariable analysis, basic science research (OR 2.84, 95% CI 1.44-5.61 as compared to clinical research) and the scientific meeting [OR 2.87, 95% CI 1.60-5.15 (ASN); OR 1.92, 95% CI 1.07-3.45(ERA) as compared to NKF] were significantly associated with full publication. CONCLUSIONS: Almost two-fifths of abstracts presented at three major nephrology meetings are subsequently published in peer-reviewed journals. Basic science content and the meeting at which the abstract was presented are associated with publication. Further research is needed to ascertain the impact of other important factors on abstract publication rates to address publication bias in the renal literature.
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 | 0.050 | 0.256 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.021 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".