Tendencies of Recreational Landscape Formation in Southeastern Baltic Seaside Resorts after 1990. Case of the Palanga Resort
Bibliographic record
Abstract
Abstract The goal is to analyze the tendencies of the formation of recreational landscape of the Palanga resort and, after reviewing the planning experiences of other south-eastern Baltic resorts, present measures for landscape optimization. To achieve this, an analysis of changes of the seaside recreational landscape after 1990, the current state of resorts, scientific literature, and seaside resort planning was conducted. After assessing the changes in the recreational landscape, it has been noticed that for a quarter of the last century, planning of seaside resorts was aimed at attracting and accommodating an increasing number of holidaymakers, which caused an ever increasing need to intensify the construction in the territories, increasing the scale of buildings, and urbanizing natural territories without taking into consideration the existing natural and cultural environment. Natural, anthropogenic and social factors are affecting the recreational landscape of seaside resorts, which are important in the context of resort development and regional development. The article presents the means of Palanga resort optimization based on these factors.
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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 | 0.001 | 0.000 |
| 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".