Top cited articles in concussion: A bibliometric analysis of the state of the science
Bibliographic record
Abstract
Objective Citation analyses identify the most-cited publications in a given field, which aids in understanding areas of the literature that are well-developed and those where additional research is required. Our objective was to perform a citation analysis in concussion to understand the state of the science from a bibliometric perspective. Design We performed a keyword search for articles related to concussion in Harzing's Publish or Perish, which scrapes Google Scholar for citation metrics. This approach was used to identify the 50 articles with the most lifetime citations as well as the 50 articles with the highest citation rate. Main outcome measures Citations and citation rates. Results Per our citation analysis, we found that concussion guidelines are among the most cited publications (comprising ≥20% of each citation cohort), yet there is a dearth of widely cited clinical trials to inform them; only one randomized trial (studying the effects of rest following concussion) was included in our citation analysis. The majority of study designs (≥40% of each citation cohort) were cross-sectional. Concussion recovery and secondary complications of concussion were common study topics, with ≥20% of publications in each citation cohort focused on these issues. The publications included in our analysis were authored by 596 authors from only 12 countries, suggesting a lack of global representation in concussion research. Conclusions Existing reviews and consensus statements have called for additional, high-quality research in concussion; our citation analysis quantifies this need. Further, although concussion is a global problem with its incidence and burden increasing in the developing world, our citation analysis demonstrates that the most-cited and discussed articles in concussion are published by authors from only 12 countries. Going forward, to address the global problem that is concussion, a more global research perspective is called for.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | MetaresearchBibliometrics Domain: Methods · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | high |
| gpt | BibliometricsScholarly communication Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Other design | high |
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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.031 | 0.201 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.
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".