ОСОБЕННОСТИ РАЗВИТИЯ КАЛУЖСКОГО ФАРМАЦЕВТИЧЕСКОГО КЛАСТЕРА В УСЛОВИЯХ ВНЕШНИХ ВЫЗОВОВ: ПАНДЕМИЯ КОРОНАВИРУСА
Bibliographic record
Abstract
Одним из важнейших факторов развития внешнеторговой деятельности Калужской области является фармацевтический кластер. В статье описано влияние пандемии коронавируса на социально-экономическое развитие фармкластера в 1 квартале 2020 года включающая в себя: внесение нормативных поправок в законодательную базу в связи с пандемией, переход торговли в онлайн режим, статистические данные экспорта и импорта за 1 квартал, а также изменения в маркировке фармпродукции.One of the most important factors in the development of Kaluga region's foreign trade activity is the pharmaceutical cluster. The article describes the impact of the coronavirus pandemic on the socio-economic development of the pharmaceutical cluster in the 1st quarter of 2020, including: regulatory amendments to the legislative framework in connection with the pandemic, the transition of trade to online mode, export and import statistics for the 1st quarter, as well as changes in the labeling of pharmaceutical products.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.006 |
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".