Insights for a changing world Canada’s Anti-Money Laundering & Anti-Terrorist Financing Requirements – A Guide for Chartered Accountants NOTICE TO READER
Bibliographic record
Abstract
This Guide has been prepared to assist CAs in understanding Canada’s Anti-Money Laundering and Anti-Terrorist Financing Legislation. It has not been adopted, endorsed, approved, disapproved or otherwise acted upon by a Board, the governing body or membership of the CICA or any provincial Institute/Ordre. The Guide is not intended to provide legal advice. Neither the CICA nor the individuals involved in its preparation can accept any responsibility for reliance on the contents of this Guide. Readers should consult the Proceeds of Crime (Money Laundering) and Terrorist Financing Act, as well as the supporting Regulations. For additional guidance, readers should also consult the FINTRAC office consolidation of the Act, the FINTRAC office consolidation of the regulations, and the FINTRAC Guidelines.
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.008 | 0.003 |
| Scholarly communication | 0.015 | 0.006 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.025 | 0.009 |
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".