The impact of prescription opioids on all-cause mortality in Canada
Bibliographic record
Abstract
An influential study from the United States generated considerable discussion and debate. This study documented rising morbidity and mortality in midlife among white non-Hispanic Americans in the 21st century, with clear linkages of all-cause mortality to increasing rates of poisonings, suicides and chronic liver disease deaths. All of these causes of deaths are strongly related to the use of legal and illegal substances, but the study stressed the importance of prescription opioids. Given the similarities between the United States and Canada in prescription opioid use, the assessment of similar all-cause mortality trends is relevant for Canada. As this commentary highlights, the all-cause mortality shifts seen in the United States cannot be seen in Canada for either sex or age groups. The exact reasons for the differences between the two countries are not clear, but it is important for public health to further explore this question.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 | 0.043 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.004 | 0.001 |
| Research integrity | 0.018 | 0.019 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".