Bibliographic record
Abstract
Objectives : The purpose of this study was to make a comparative analysis of the websites of dental office from different countries to provide some information for the quality evaluation of the websites of dental office. Methods : Two hundred twenty-four dental websites were selected by using Yahoo, one of the international portal sites, which included 59 from the United States, 50 from the United Kingdom, 54 from Canada, and 61 from Korea. Results : 1. As results of the credibility of the websites, the Canadian websites were most reliable, followed by the American websites, the English websites and the Korean ones(p<0.005). 2. As results of the complementarity of the websites, the Korean websites were most interactive, followed by the American websites, the English websites, and the Canadian ones(p<0.001). 3. As results of the accessibility of use of the websites, the Korean websites were easiest to use, followed by the American websites, the Canadian websites, and the English ones(p<0.001). 4. As results of the update of the websites from the nations, the Korean websites were most sustainable, followed by the English websites, the Canadian websites and the American ones(p<0.05). 5. When the overall quality of the dental office websites was assessed, the Korean websites were the best, followed by the Canadian websites, the American websites and the English ones(p<0.001). Conclusions : In order to make accurate oral health information more accessible to people in general, prolonged research efforts should be continued for the evaluation of the quality of dental office websites, and the development of standard international evaluation criteria is required as well.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.013 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".