The 17th Theoretical and Practical Conference “Opportunities For Development of Regional Studies of Siberia and Neighbouring Areas”
Bibliographic record
Abstract
These Conference Proceedings contain the selected papers of the 17th theoretical and practical conference with international participation "Opportunities for development of tourism of Siberian region and neighboring areas" which was held from 30 October to 1 November 2018 in Tomsk. The conference was organized by National Research Tomsk State University. It was supported by the Tomsk regional branch of the Russian geographical society, the Department of culture and tourism of Tomsk region, the Department of General education of Tomsk region and the Tomsk city Administration. The Program Committee included Professor of the Carleton University (Canada) R.E. Ernst, Professor of the Tomsk state University Nina S. Evseeva, Professor of the Tomsk Polytechnic University Natalia A. Kolodiy, head of the Department of local history and tourism of the Tomsk state University Larisa B. Filandysheva, head of the Department of recreational geography, tourism and regional marketing of the Altai state University Alexander G. Redkin, head of the Laboratory of Self-Organization of Geosystems Institute of Monitoring of Climatic and Ecological Systems of the Siberian Branch of the Russian Academy of Sciences Pavel S. Borodavko and other famous scientists.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.035 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".