10.5937/jaes12-7169 = Modernization of model for initiation of investment projects as a factor of balanced maintenance of region’s investment-innovational activity
Bibliographic record
Abstract
In recent decades, because of globalization, development of social, information technologies and some other reasons cities and regions of the world have received the brand new possibilities of economic and cultural development. Barcelona and Sydney, Vancouver and Helsinki, separate parts of Zurich and Strasburg, alone with spread row of provincial and little-known towns and regions, took advantages of new opportunities and obtained a high-capacity inflow of investments and tourists, increase of business and local communities’ activity, new political weigh and cultural significance. As a result, at these territories, the quality of life increased, as much as integration degree of political, business, and cultural structures into national and international area, including investment. In Russia new possibilities were being explored by each territory according to its opportunities, within the programs of Russia’s regions innovational development. Nowadays, because of accumulated international and domestic experience, we can easily say, that the time has come to expand the limits by embracement of technological innovational activity by investment and social-cultural approaches to development and branding of territories.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.790 | 0.729 |
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".