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Record W4410507785 · doi:10.54613/ku.v14i.1116

O‘ZBEKISTON RESPUBLIKASIDA AGRAR SOHA FAOLIYATINING IQTISODIY RIVOJLANISH TENDENSIYALARINI STATISTIK USULLARDAGI TAHLILI

2025· article· uz· W4410507785 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueQO‘QON UNIVERSITETI XABARNOMASI · 2025
Typearticle
Languageuz
FieldEconomics, Econometrics and Finance
TopicEconomic and Industrial Development
Canadian institutionsKootenay Association for Science & Technology
Fundersnot available
KeywordsMathematics

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.735
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.002

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.

Opus teacher head0.020
GPT teacher head0.210
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it