Scientific production of an oral implantology journal: a 5-year bibliometric study
Bibliographic record
Abstract
Oral implantology is a science in constant evolution, with a considerable number of articles being published every year in scientific journals. Publications can be analyzed through bibliometric analysis, thus observing the evolution and trends of the articles published in the journal. To evaluate, through bibliometric analysis, the scientific production of Clinical Implant Dentistry and Related Research (CIDRR) and its evolution and trends in the last 5 years (2016-2020).All articles published in CIDRR in the last 5 years were reviewed and classified according to the year of publication, volume, number, the number of authors, demographic data of the first and last author, the geographical scope of the article, the number of affiliations of the authors, research topic, type of study, and study design. The association between these variables and citation counts was also analyzed. 599 articles were analyzed. 77.4% were authored by 4-6 authors, obtaining 78.4% from 1 to 3 different affiliations. Male researchers predominated in both the first and last authorship. China showed the highest number of publications when comparing the origin of the authors' affiliations individually; however, most researchers (40.9%) were from the European Union (EU)-Western Europe area. The most studied topic was the implant/abutment design/treatment of the surface (19.1%). Clinical research articles accounted for 92.99% of the publications, of which cross-sectional observational studies prevailed (21.7%). The presence of articles from the United States of America-Canada and EU-Western Europe was positively correlated with the impact factor. This study revealed an increasing trend in Asian research production, particularly Chinese, whereas production of European origin showed a decrease. Clinical studies increased their relative weight to the detriment of translational ones. A growing tendency in the relative weights of female authors was appreciated. Journal citations were associated with certain study variables.
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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 | 0.006 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.184 | 0.429 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".