Bibliographic record
Abstract
the harm related to active and passive smoking. Successes in this endeavor have been achieved; however, other types of substance abuse are on the increase. These emerging addictions have been outside of our field of attention, and in some communities their use is far more prevalent than that of smoking. In Ontario, for instance, the rate of smoking among students in grades 7 to 12 was 8.7%, whereas the rate of abusing painkillers was 15.2% (opioid 14%, oxycontin 1.2%). 3 Of importance is that 19% of students indicated fairly easy or very easy access to prescription painkillers without visiting a doctor. In 2009, 0.6% of Canadians aged 15 years and older reported having used a psychoactive pharmaceutical to get high during the past year. The use of prescription opioids to get high (with annual prevalence of 0.4%) overshadows the use of heroin (annual prevalence of 0.3%), and was greater than the use of stimulants (0.1%), and sedatives and tranquilizers (0.2%). 4
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 | 0.001 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.055 | 0.008 |
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".