Geographic variation in the number of authors on scientific abstracts.
Bibliographic record
Abstract
OBJECTIVE: To determine if there was statistically significant geographic variation in the number of authors on abstracts of the 1999 Radiological Society of North America (RSNA) Scientific Assembly. METHODS: Information on type of presentation, number of authors listed in each presentation and country of origin was obtained for 2450 abstracts from the 1999 RSNA Scientific Assembly (1292 for scientific sessions, 1158 for scientific exhibitions). RESULTS: In scientific sessions, there were significantly more multiauthor (> 6 authors) presentations from Japan (32%, p < 0.001) and Germany (19%, p = 0.004) than there were from North America (United States and Canada) (11%). There were also significantly more multiauthor scientific exhibitions from Japan (29%, p < 0.001) than from North America (9%). Overall, the percentages of multiauthor presentations from Japan (30%, p < 0.001) and Germany (18%, p < 0.001) were significantly higher than those from North America (10%). CONCLUSION: There seems to be significant geographic variation in the number of authors credited on scientific presentations.
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 | 0.008 | 0.050 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.010 | 0.020 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".