Comparison of dental information websites in some nations
Bibliographic record
Abstract
Objectives : The purpose of this study was to compare the dental information websites in some nations and to provide the basic data for clinical application. Methods : Two hundred twenty-four dental websites were chosen by using Yahoo search engine. The websites included 59 from the United States, 50 from the United Kingdom, 54 from Canada, and 61 from Korea. The survey was conducted from August 15 to September 30, 2011. Results : The guidance of medical treatment expenses was the most sustainable in the United Kingdom and followed by the United States, Canada, and Korea(p<0.001). Korean dental information website provided the visitor's message. The United Kingdom provided the best type of FormMail and the United States, Canada and Korea also provided(p<0.001). Korean dental information website showed the best types of messages and was followed by the United States, Cadana and the United Kingdom. Korean dental information had the best type of FormMail(p<0.001). Conclusions : In order to make the accurate access to the dental health information website, it is necessary to provide the easy access and continuous research efforts to the information system.
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".