Regional Agriculture, Food Supply Systems and Competitiveness of Agriculture Prodiction Industries in Stavropol Territory
Bibliographic record
Abstract
The article is devoted to the issue of ensuring the competitiveness of the agriculture and food system currently present in Stavropol Territory. Provision of the local population with locally manufactured food products in sufficient quantities and of the appropriate quality is one of the main challenges for the regional authorities. Assesment for the most advantageous trends for developing agriculture sector in Stavropol Krai considering its supply security, production costs and market demands for the manufactured products is quite essential. Results of the assesment ensured preparation of the market maps for Stavropol Territory with reference to the main product groups, that allowed to rank them in accordance with the identified indicators. To assess efficiency of the industries, the analysis of the investment strategic positions within the main agriculture product groups was prepared and involved imlementation of adjusted BCG matrix. Based on the obtained data the following was prepared: ranking for agricultural industries considering their socio-economic importance for the Stavropol Territory, and recommendations on the feasible trends for particular industries.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".