Bibliographic record
Abstract
The tourism with its widest range of resource interests acts as a counterbalance to modern tendencies of social and economic space compression. In Russian regions there is a growing interest in «areal development» of tourism, which requires higher degree of territorial organization than the «site development». Fractional zoning is a geographical tool for involving the entire region in the tourist processes, but it still has a low applied value for tourism in Russia. The provinces of Canada are the world leaders in spatial delimitation for the purpose of practical tourism. All ten provinces of Canada actively use fractional tourist zoning, basing it on different principles, however. The Canadian experience of representing provinces in tourist mosaics should be taken into the account in Russian regions. Basing on the results of our studies and the experience from the Canadian provinces it is necessary to allocate the following tourist areas in the Perm region: North Urals, Mining Urals, Preduralje, Parma, Upper Kama, Middle Kama and Lower Kama.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 0.007 |
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".