Report summary – Mood and Anxiety Disorders in Canada, 2016
Bibliographic record
Abstract
Mood and Anxiety Disorders in Canada, 2016 is the first publication to include administrative health data from the Canadian Chronic Disease Surveillance System (CCDSS) for the national surveillance of mood and anxiety disorders among Canadians aged one year and older. It features nationally complete CCDSS data up to fiscal year 2009/10, as well as trend data spanning over a decade (1996/97 to 2009/10). The data presented in this report, and subsequent updates, can be accessed via the Public Health Agency of Canada's Chronic Disease Infobase Data Cubes at www.infobase.phac-aspc.gc.ca. Data Cubes are interactive databases that allow users to quickly create tables and graphs using their Web browser. The report demonstrates the Public Health Agency of Canada's commitment to improving data collection and reporting about mental illness, as recommended within Changing Directions, Changing Lives - The Mental Health Strategy for Canada.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.012 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.018 | 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".