An overview of IRFS on Canadian GAAP — Self-organizing maps (SOMs)<sup>MS</sup>
Bibliographic record
Abstract
This study provides an overview of International Financial Reporting Standards (IFRS) and highlights implications on Canadian Generally Accepted Accounting Principles (CGAAP) besides the influence IFRS will have on their future representation of Financial Statements - Annual Reports. However, the IFRS has developed a conceptual framework for the preparation and presentation of Financial Statement, and Financial Reporting in order to harmonize accounting standards that are principal-based, internally consistent, and internationally regulated. Then it became apparent that, conversion to IFRS would lead to better comparability and uniformity of financial statements and it could also become sensitive to challenges in application and adoption of their standards. This paper was designed to identify these changes with the use of Neutral Network, such as Self Organization Maps (T Kohoen's SOMs 1997, 2001) as a financial tool to review financial performance of a company over a period of twelve years - pre and post IFRS along with financial ratios, per se Profitability and other ratios such as, Liquidity, Leverage & Coverage, and Efficiency of a Canadian Company.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.010 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.014 | 0.005 |
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".