MétaCan
Menu
Back to cohort
Record W4408161187 · doi:10.55439/ist/vol1_iss2/50

ANALYSIS OF THE FORM OF RECEIVABLES AND ACCOUNTS PAYABLES OF ENTERPRISES AND ORGANIZATIONS IN THE REPUBLIC OF UZBEKISTAN FOR THE QUARTER OF 2024

2025· article· en· W4408161187 on OpenAlexaboutno aff
Khalikulova Yulduz Panji qizi, Abdullayeva Fazilat Khazratovna

Bibliographic record

VenueInnovation Science and Technology · 2025
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSustainability and Innovation in Business
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Accounts payableAccounts receivableBusinessAccountingFinanceGeography

Abstract

fetched live from OpenAlex

This article analyzes public and private enterprises operating in the Republic of Uzbekistan, focusing on the frstand second quarters of 2023 compared to the same periods in 2024. The study examines factors influencing the excessof accounts receivable and identifes the causes of increasing accounts payable. Furthermore, several recommendationsare proposed to mitigate the growth of larger accounts payable in the future.

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.

How this classification was reachedexpand

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.398
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.027
Science and technology studies0.0000.001
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 head0.010
GPT teacher head0.267
Teacher spread0.256 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueInnovation Science and TechnologySame topicSustainability and Innovation in BusinessFrench-language works237,207