Investments and economic growth in poultry farming
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Theories of economic growth determine the leading role of investment processes. The purpose of this article is to inform the scientific community about the results of the analysis of the sectoral economic growth and investment support in the case of the poultry industry sub-sector. The analysis was carried out on the example of 493 organizations belonging to the type of activity 01.47 “Breeding of agricultural poultry”. In the course of the study, the organizations were divided into groups according to the scale of their activities, and their financial status was analyzed, as loan debts for investment projects in the poultry farming accounted for 38%. The analysis showed that the financial condition of the poultry organizations is better than the financial condition of the organizations in Russia as a whole. Also, large organizations with revenues above 2 billion rubles have better financial situation. Almost a quarter of organizations in the poultry farming are large and medium-sized ones (23.6%). They have revenues of 800 million rubles, which allows them making the necessary investments.
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.
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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it