Treatment of Opioid Dependence: Harm Reduction, Palliation, or Simply Good Medical Practice?
Bibliographic record
Abstract
Opioid alkaloids have been used medicinally for centuries as analgesics, for their antidiarrheal and antitussive properties, and as hypnotics. Opioids were initially derived from the poppy plant (Papaver somniferum) by the ancients of the Mediterranean Basin. Written records of the medicinal uses of opioids date to before the time of Hippocrates (460–377 BC). Paracelsus prescribed opium in a medicinal drink of wine and spices in the 16th century. Sir William Osler, the renowned Canadian physician of the late 1800’s remarked that opium was “God’s own Medicine”. Opioids are considered superb medications by modern physicians, who widely prescribed them still and for the most part without significant adverse consequences. Yet there is a “dark side ” to opioids for those who
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.009 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.005 | 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".