La gestión de tesorería y su relación con los pagos a proveedores de la unidad ejecutora de Ucayali - Contamana, año 2023
Bibliographic record
Abstract
The objective of this research was to determine the relationship between treasury management and payments to suppliers of the Executive Unit of Ucayali-Contamana, year 2023. The research methodology comprised a basic type, correlational and non-experimental design, quantitative approach, probabilistic sampling, as well as a population and sample of 50 and 45, respectively, among workers linked to treasury management functions in the Ucayali-Contamana Executing Unit, as well as people linked to the process of providing goods and services to the entity (suppliers). The main results demonstrated the importance of treasury management in the Ucayali-Contamana Executing Unit being carried out according to a series of principles, the implementation of financial control and the development of effective collection and payment management, as a basis for compliance with payments to the entity's suppliers. Finally, the main conclusion was to determine that there is a significant relationship between treasury management and payments to suppliers of the Ucayali-Contamana Executing Unit, year 2023. This premise is consistent with the Spearman correlation index 0.828 for the case of the general hypothesis.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".