Highly cited works in neurosurgery. Part II: the citation classics
Bibliographic record
Abstract
OBJECT: The term "citation classic" has been used in reference to an article that has been cited more than 400 times. The purpose of this study is to identify such articles that pertain to clinical neurosurgery. METHODS: A list of search phrases relating to neurosurgery was compiled. A topic search was performed using the Institute for Scientific Information Web of Science for phrases. Articles with more than 400 citations were identified, and nonclinical articles were omitted. The journals, year of publication, topics, and study types were analyzed. RESULTS: There were 106 articles with more than 400 citations relating to clinical neurosurgery. These articles appeared in 28 different journals, with more than half appearing in the Journal of Neurosurgery or the New England Journal of Medicine. Fifty-three articles were published since 1990. There were 38 articles on cerebrovascular disease, 21 on stereotactic and functional neurosurgery, 21 on neurooncology, 19 on trauma, 4 on nontraumatic spine, 2 on CSF pathologies, and 1 on infection. There were 29 randomized trials, of which 86% appeared in the New England Journal of Medicine, Lancet, or the Journal of the American Medical Association, and half concerned the prevention or treatment of stroke. In addition, there were 16 prospective studies, 15 classification or grading systems, and 7 reviews. The remaining 39 articles were case series, case reports, or technical notes. CONCLUSIONS: More than half of the citation classics identified in this study have been published in the past 20 years. Case series, classifications, and reviews appeared more frequently in neurosurgical journals, while randomized controlled trials tended to be published in general medical journals.
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 | 0.055 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.126 | 0.263 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.001 | 0.005 |
| 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; both teacher heads agree on what is shown here.
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".