Characteristics and Trends of the Most Cited Spine Publications
Bibliographic record
Abstract
STUDY DESIGN: Bibliometric literature review. OBJECTIVE: The aim of this study was to recognize and analyze the most frequently cited manuscripts published in the journal Spine. SUMMARY OF BACKGROUND DATA: Although the journal Spine is considered a premiere location for distributing influential spine research, no previous study has evaluated which of their publications have had the most impact. Knowledge and appreciation of the most influential Spine publications can guide and inspire future research endeavors. METHODS: Using the Scopus database, the 100 most cited articles published in Spine were accessed. The frequency of citations, year of publication, country of origin, level-of-evidence (LOE), article type, and contributing authors/institutions were recorded. The 10 most cited articles (per year) from the past decade were also determined. RESULTS: "Guidelines For The Process Of Cross-Cultural Adaptation Of Self-Report Measures" by Beaton DE was the most cited article with 2960 citations. 2000 to 2009 (n = 46) was the most productive period. A LOE of III (n = 35) followed by II (n = 34) were the most common. Deyo RA (n = 8), Bombardier C (n = 6), and Waddell G (n = 6) produced the most articles. University of Washington (n = 8) and University of Toronto (n = 8) ranked first for institutional output. Clinical Outcome (n = 28) was the most recurring article topic. The United States (n = 51) ranked first for country of origin. CONCLUSION: Using citation analysis as an objective proxy for influence, certain publications can be distinguished from others due to their lasting impact and recognition from peers. Of the top cited Spine publications, many pertained to clinical outcomes (28%) and had a LOE of I, II, or III (60%). Although older publications have had longer time to accrue citations, those in the most recent decade comprise this list almost 2:1. Knowledge of these "classic" publications allows for a better overall understanding of the diagnosis, management, and future direction of spine health care.Level of Evidence: 3.
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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 | 0.002 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.010 | 0.198 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".