National Research Council Canada: quarterly financial report for the quarter ended December 31, 2016 (unaudited)
Bibliographic record
Abstract
The Government of Canada uses financial information to support decision making, for policy development, for service delivery and for historical reference. These financial statements have been prepared to respond to these requirements. This Departmental Quarterly Financial Report (QFR) reflects the results of the current fiscal period in relation to the Main Estimates, Supplementary Estimates (A) and Supplementary Estimates (B). The QFR should be read in conjunction with the Main Estimates, Supplementary Estimates (A) and Supplementary Estimates (B) as well as Canada’s Economic Action Plan (Budget 2012, Budget 2013, Budget 2014, Budget 2015 and Budget 2016). They have been prepared by management as required by section 65.1 of the Financial Administration Act (R.S.C., 1985, c. F-11) and in the form and manner prescribed by the Treasury Board of Canada Secretariat. Although these statements have not been subject to an external audit or review, the National Research Council Canada (NRC) attests that they are an accurate and true reflection of the financial position for the period ended December 31, 2016.
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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 | 0.010 | 0.037 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.013 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.012 | 0.003 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.105 | 0.108 |
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".