Publication rates of abstracts presented at major interventional radiology conferences
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
PURPOSE: We aimed to determine the publication rate and factors predictive of publication of oral presentations at the annual meetings of the Cardiovascular and Interventional Radiology Society of Europe (CIRSE) and the Society of Interventional Radiology (SIR). METHODS: Keywords and authors from oral presentation abstracts at the 2012 CIRSE and SIR annual meetings were used to search PubMed and GoogleScholar for subsequent publication. Logistic regression was performed to identify whether number of authors, country of origin, subject category, methodology, study type, and/or study results were predictive of publication. RESULTS: A total of 421 abstracts (CIRSE-126, SIR-295) met the inclusion criteria. The overall publication rate across both conferences was 44.9%. Time from conference presentation to publication was 15±8.9 months for CIRSE and 16.3±8.8 months for SIR (P > 0.05), with a combined time interval of 15.9±8.8 months for both. The median impact factor of published abstracts was 2.075 (interquartile range, 2.075-2.775) for CIRSE and 2.093 (2.075-2.856) for SIR (P > 0.05). The most common country of origin for published abstracts was Germany (27.1%) at CIRSE and the United States (69%) at SIR. Logistic regression did not identify factors that were predictive of future publication. CONCLUSION: Publication rates were similar for CIRSE and SIR. Factors such as country of origin, topic of study and study results were not predictive of future publication. Authors should not be discouraged from submitting their work to journals based on these factors.
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.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it