The academic productivity and impact of the University of Toronto Neurosurgery Program as assessed by manuscripts published and their number of citations
Bibliographic record
Abstract
OBJECT: Recent works have assessed academic output across neurosurgical programs using various analyses of accumulated citations as a proxy for academic activity and productivity. These assessments have emphasized North American neurosurgical training centers and have largely excluded centers outside the United States. Because of the long tradition and level of academic activity in neurosurgery at the University of Toronto, the authors sought to compare that program's publication and citation metrics with those of established programs in the US as documented in the literature. So as to not rely on historical achievements that may be of less relevance, they focused on recent works, that is, those published in the most recent complete 5-year period. METHODS: The authors sought to make their data comparable to existing published data from other programs. To this end, they compiled a list of published papers by neurosurgical faculty at the University of Toronto for the period from 2009 through 2013 using the Scopus database. Individual author names were disambiguated; the total numbers of papers and citations were compiled on a yearly basis. They computed a number of indices, including the ih(5)-index (i.e., the number of citations the papers received over a 5-year period), the summed h-index of the current faculty over time, and a number of secondary measures, including the ig(5), ie(5), and i10(5)-indices. They also determined the impact of individual authors in driving the results using Gini coefficients. To address the issue of author ambiguity, which can be problematic in multicenter bibliometric analyses, they have provided a source dataset used to determine the ih(5) index for the Toronto program. RESULTS: The University of Toronto Neurosurgery Program had approximately 29 full-time surgically active faculty per year (not including nonneurosurgical faculty) in the 5-year period from 2009 to 2013. These faculty published a total of 1217 papers in these 5 years. The total number of citations from these papers was 13,434. The ih(5)-index at the University of Toronto was 50. CONCLUSIONS: On the basis of comparison with published bibliometric data of US programs, the University of Toronto ranks first in terms of number of publications, number of citations, and ih(5)-index among neurosurgical programs in North America and most likely in the world.
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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 | 0.016 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.018 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".