Relación del resultado neto del ejercicio con otros ingresos y otros gastos en una Caja Municipal de Ahorro y Crédito, 2018-2022
Bibliographic record
Abstract
The objective is to decree how the net result of the year is related to other income and other expenses in a Municipal Savings and Credit Fund (CMAC), 2018-2022. It was based on a quantitative, transectional, descriptive and correlational approach. The population was the financial statements, the sample of 20 quarters with intentional sampling. The documentary analysis and the research sheet instrument were carried out. The result showed that the relationship between the net result of the year with other income and other expenses, in a CMAC, is inverse although not significantly. This finding arose due to dissimilar balances; That is, the increases or decreases in both variables do not coincide, from one quarter to the next. However, in the 20 quarters, most of the time the results showed inverse balances, since the net result for the year was reduced compared to the amounts achieved in pre-pandemic times, while the differential of other income less other expenses improved since They stopped being negative, after the problems of COVID-19 were overcome. It was concluded that the relationship between the net result of the year with other income and other expenses is not significant, in a CMAC, but it is weakly inverse.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".