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Record W4392871065 · doi:10.54613/ku.v9i9.830

INFLUENCE OF THE VOLUME OF INDUSTRIAL PRODUCTION IN UZBEKISTAN ON THE IMPORT TREND

2023· article· en· W4392871065 on OpenAlex
Sabirov Khasan Nusratovich, Akbarova Asidaxon

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 · 2023
Typearticle
Languageen
FieldEngineering
TopicWater and Wastewater Treatment
Canadian institutionsNordic Life Science Pipeline (Canada)
Fundersnot available
KeywordsProduction (economics)Industrial productionEconometric modelEconometricsTest (biology)Regression analysisEconomicsStatisticsMathematicsMacroeconomics

Abstract

fetched live from OpenAlex

The main goal of the scientific research is to study the interaction of industrial production in Uzbekistan with the volume of imports, and statistical data for the period of 2010-2021 were used in the research. First, a summary of the scientific articles on the topic was shown, and an econometric model was used to conduct the research. During the research, a multi-factor correlation-regression analysis was conducted and a model was created. Fisher test and Durbin-Watson test were used. In the results of scientific research, it was found that there is no connection between industrial production and import. At the end of the article, proposals and conclusions are given on the rapid development of industrial production and reduction of imports.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.621
Threshold uncertainty score0.294

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.015
GPT teacher head0.179
Teacher spread0.164 · 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