O‘ZBEKISTON RESPUBLIKASIDA AGRAR SOHA FAOLIYATINING IQTISODIY RIVOJLANISH TENDENSIYALARINI STATISTIK USULLARDAGI TAHLILI
Bibliographic record
Abstract
Ushbu maqolada O‘zbekiston Respublikasida agrar soha faoliyatining iqtisodiy rivojlanish tendensiyalari statistik tahlillar asosida o‘rganilgan. Mamlakatning asosiy hududlari bo‘yicha qishloq xo‘jaligi mahsulotlari, ayniqsa, dehqonchilik mahsulotlari yetishtirish ko‘rsatkichlari yillik o‘sish sur’atlari orqali tahlil qilingan. 2021–2024 yillar oralig‘idagi real statistik ma’lumotlar asosida ishlab chiqarish hajmi, tashkilotlar ulushi, resurslardan foydalanish darajasi, suv ta’minoti, va hududiy tafovutlar ko‘rib chiqilgan. Tahlillar natijasida agrar sohada mavjud muammolar aniqlanib, ularni bartaraf etish va sohaning barqaror rivojlanishini ta’minlashga qaratilgan amaliy takliflar ilgari surilgan. Tadqiqot yakunida ilmiy asoslangan xulosa va tavsiyalar shakllantirildi.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.050 | 0.010 |
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".