Academic Productivity in Hepatopancreatobiliary Surgeons: Identifying Benchmarks Associated With Rank in North America
Bibliographic record
Abstract
Background Academic achievement is an integral part of the promotion process; however, there are no standardized metrics for faculty or leadership to reference in assessing this potential for promotion. The aim of this study was to identify metrics that correlate with academic rank in hepatopancreaticobiliary (HPB) surgeons. Materials and Methods Faculty was identified from 17 fellowship council accredited HPB surgery fellowships in the United States and Canada. The number of publications, citations, h-index values, and National Institutes of Health (NIH) funding for each faculty member was captured. Results Of 111 surgeons identified, there were 31 (27%) assistant, 39 (35%) associate, and 41 (36%) full professors. On univariate analysis, years in practice, h-index, and a history of NIH funding were significantly associated with a surgeon’s academic rank ( P < .05). Years in practice and h-index remained significant on multivariate analysis ( P < .001). Discussion Academic productivity metrics including h-index and NIH funding are associated with promotion to the next academic rank.
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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 | 0.002 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".