Publication rate of abstracts presented at the Canadian society of otolaryngology- head and neck surgery annual meetings: A five year study 2006–2010
Bibliographic record
Abstract
BACKGROUND: To determine the rate of publication in a peer-reviewed journal for all oral presentations made at the Canadian Society for Otolaryngology- Head and Neck Surgery's Annual Meetings from 2006-2010. METHODS: All abstracts were searched by keywords and authors' names in Medline via PubMed and Google Scholar. Authors of presented abstracts not found to be published were contacted directly for further information. RESULTS: 50.5% of presented abstracts (n = 198) were subsequently published with an average time to publication of 21 months. For those abstracts found not to be published 74.6% (n = 167) of authors responded with further information about their research, 66% (n = 89) of abstracts with author response that were not published were never submitted for publication. Authors' main reasons for not publishing were that the research was still in process (34%, n = 21) or that a resident or fellow working on the project "had moved on" (26%, n = 16). CONCLUSION: The publication rate for the Canadian Society for Otolaryngology- Head and Neck Surgery's Annual Meetings from 2006-2010 is within the range reported by other conferences and specifically other Canadian conferences in different specialties; however, roughly half of presentations went on to be published. The main barrier to publication was bringing projects to the submission stage and not rejection by journals. Resources such as more time for research or personnel to coordinate projects may result in a greater rate of project completion.
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 | 0.018 | 0.082 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.020 | 0.021 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".