The Effect of the COVID-19Pandemic on Dental Tourism in Croatia
Bibliographic record
Abstract
Dental tourism is based on providing dental services outside the home country at more favourable prices but with added value in tourist offers and arrangements. Croatia has become a destination for affordable and at the same time quality dental tourism due to low prices, high quality, and natural beauties. In addition to dental services, most clinics offer transportation and accommodation. Dental tourists want to combine dental services with vacation, which makes Croatia a desirable destination precisely because of the natural beauty and abundance of rich content. For this reason, many Croatian dentists have recognized dental tourism as an additional source of income or as their primary business orientation. Although clinics operating within dental tourism are located throughout Croatia, the most significant number is in Zagreb, Rijeka, and Split. Patients mostly come from developed countries such as Italy, Austria, Germany, UK, Ireland, Japan, Canada, and the USA, where dental procedures are not as affordable. Dental tourism in Croatia had exponential growth until March 2020, when, for the first time, it faced a global problem and was challenged in the form of the COVID-19 pandemic.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 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; 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".