The funding sources of implantology research in the period 2008‐2017: A bibliometric analysis
Bibliographic record
Abstract
BACKGROUND: Implant dentistry is subject to major economic pressures as a result of the growth in the manufacturing and commercialization of dental implants. PURPOSE: To examine research funding in implant dentistry by means of a bibliometric analysis of articles indexed in Web of Science (WoS) published during the period 2008-2017. MATERIALS AND METHODS: The search was conducted applying the truncated term "implant*" in the WoS dentistry area. Only items labeled as "article" or "review" were selected. Records were manually refined and normalized to unify terms and to remove typographical, transcription, and/or indexing errors. RESULTS: A total of 14 255 records were identified for analysis. About 5002 of the 14 255 published works received funding. Of these, 85.9% of funded research articles received at least one citation. Of the 7733 funding entities mentioned, 29.8% were government entities, 25% NGOs and Foundations, 23.7% private companies, 19.6% academic entities, and 1.9% hospitals and research centers. Clinical Oral Implants Research and the International Journal of Oral & Maxillofacial Implants published the highest numbers of funded articles. CONCLUSIONS: This study revealed an overall increase in the funding of research in implant dentistry in recent years. Funded articles were cited more frequently and published in journals with higher impact factors.
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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 | BibliometricsMetaresearch Domain: Incentives · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Observational | low |
| gpt | BibliometricsMetaresearch Domain: Incentives · 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 | 0.298 | 0.062 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.397 | 0.815 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.006 | 0.002 |
| Research integrity | 0.001 | 0.004 |
| 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, unvalidatedLabeled directly by 2 models reading the full record.
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".