Development of Sremski Karlovci wine tourism and integration in the regional tourism offer
Bibliographic record
Abstract
Integration and globalisation processes are unavoidable in all fields of business economy, including tourism. Potential success of wine tourism in Sremski Karlovci should be based on diversification of products that entails an influx of tourism and winemaking into other fields of economy. During the development of wine tourism offer, it would be advisable to consult the experiences of the developed wine region and to use their models, which is done in this paper, via benchmark analysis of offers of Sremski Karlovci wineries with those of the Ontario region (Canada) and the place of Villány (Hungary). The goal of this paper is to establish the possible directions of development of the integral product of wine tourism of Sremski Karlovci as a prerequisite for integration into the regional tourism offer. The research indicates that wine tourism offer of Sremski Karlovci is underdeveloped. A large number of product diversification fields are not recognised. The future development of Sremski Karlovci wineries should be based on conquering of those very fields. Such a tourism product could more easily be integrated into the regional wine tourism offer.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".