Commentary All editorial matter in CMAJ represents the opinions of the authors and not necessarily those of the Canadian Medical Association.
Bibliographic record
Abstract
Depression is a major public health problem, which ispredicted to be second only to cardiovascular dis-ease as the leading cause of disease-related disabil-ity worldwide by 2020.1 It is already the leading cause of disease-related disability among women, and in most coun-tries, the prevalence of depression among women from pu-berty to menopause is twice that among men of the same age.1 In Canada, the 12-month prevalence of depression among people aged 18–65 is 4.8 % (5.9 % of women, 3.7 % of men), with the sex-based disparity being even greater during the child-bearing years.2 Certain subgroups of Canadians are at even higher risk. For example, Aboriginal people who live off-reserve are 1.5 times more likely than other Canadians to be depressed over a 12-month period. Depression rates are slightly higher in the United States and slightly lower in Eu-rope but follow the same sex-based pattern. In addition to personal suffering, depression has a detrimental effect on
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.000 |
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 teacher head, 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".