Overview, Trends, and Collaboration on Immunization, Vaccination, and Immunomodulation Therapies for Periodontitis: A Scientometric Study
Bibliographic record
Abstract
AIM: To identify patterns and trends in the field of immunization, vaccination, and immunomodulation therapies for periodontitis. MATERIALS AND METHODS: Metadata were collected from the Scopus database on publications related to these topics from January 1986 to February 2024. Several types of papers were included in this study, a total of 22 publications. Data were extracted from relevant publications and loaded into SciVal for analysis that were used to identify trends and patterns in the data, including cross-country collaboration, thematic evolution, and keyword distribution. RESULTS: Mohsen Amin of Tehran University of Medical Sciences in Iran and S. Aadil Ahamed and Annie Kitty George of Saveetha Institute of Medical and Technical Sciences in India were found to be notable contributors in this field. India leads in terms of academic paper production, followed by Iran and China. The journals Expert Review of Vaccines and International Immunopharmacology have published significant papers in this field. CONCLUSIONS: According to Lotka's Law, most authors have written only one paper, reflecting the distribution of productivity in many academic and scientific fields. Collaborations were observed between Iran and Canada, Korea and New Zealand, and the United States and Belgium. This study provides useful insight into the predominant trends and patterns in the scientific literature in the field of immunization, vaccination, and immunomodulation therapies for periodontitis. CLINICAL SIGNIFICANCE: . Overview, Trends, and Collaboration on Immunization, Vaccination, and Immunomodulation Therapies for Periodontitis: A Scientometric Study. J Contemp Dent Pract 2024;25(2):128-133.
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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 | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Not applicable | low |
| gpt | Bibliometrics Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | 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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 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".