Mejoramiento del reconocimiento de ingresos a partir de la NIIF 15 en Ecuador
Bibliographic record
Abstract
The Superintendency of Companies, Securities and Insurance on August 21, 2006 through resolu-tion 06.Q.ICI.004 established the mandatory application of International Financial Reporting Stan-dards (IFRS) in Ecuador (Superintendencia de Compañías, 2006). This resolution determines that any change or update to these international standards will be of local application and mandatory. In May 2014, the Board issued IFRS 15 referring to Income from Ordinary Activities from Contracts with Customers that provides a comprehensive framework for the recognition of income, so that the appli-cation and transition of this new standard will affect all businesses , in varying degrees according to the operation and business direction of each company, such that with an effective transition date that began on January 1, 2017, provided the entities the opportunity to carefully consider the new require-ments and solve in advance potential problems in each area that affects (Deloitte, 2017).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.002 |
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.
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; both teacher heads agree on what is shown here.
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".