Research on Research: Publication of Projects Presented at Medical Imaging Research Days Across Canada
Bibliographic record
Abstract
OBJECTIVE: Twenty-one previous studies have shown a mean presentation to publication conversion rates at radiology conferences of 26%. There have been no prior studies on publication of medical imaging residency research presentations. Our objective was to determine how many medical imaging resident research projects presented at internal program research days across Canada go on to publication. METHODS: A list of unique medical imaging resident research presentations given at program research days during the 2012-2013 to 2016-2017 academic years was generated via e-mail contact of programs or review of publicly available data on program websites. Unique resident presentations were identified and publications associated with these presentations were sought via database and Internet searching. The number of publications, publishing journals, and time to publication was determined. RESULTS: Data from 32 research days at 7 programs were assessed. A total of 287 resident presentations were identified. Of these 287 presentations, 99 had associated publications (34% presentation to publication conversation rate), with variation in presentation numbers and publication conversion rates between schools. These 99 presentations were associated with a total of 118 publications in a total of 57 different journals. Time from presentation to publication was calculable for 109 of the 118 articles. Fifteen (14%) were published before research day and 94 (86%) were published after research day with a mean time to publication of 12.3 ± 13.6 months for all articles. CONCLUSIONS: Thirty-four percent of resident research presentations at Canadian medical imaging program research days go on to publication.
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 | 0.026 | 0.069 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.000 | 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; a candidate call from one teacher head, 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".