Bibliographic record
Abstract
Opioid use disorder is a growing epidemic, with an alarming number of associated deaths. In 2014, in the United States, 18,893 lethal overdoses were related to prescription opioids and 10,574 due to heroin. Despite the growing number of treatment options for substance use disorders, which are chronic, relapsing-remitting conditions, relapse rates remain as high as 91%. In the United States, 7.5 million children reside with at least one patient who abuses drugs or alcohol. Mothers are twice as likely to lose custody of their children. They have higher rates of comorbid abuse and psychopathology and limited social supports. Child service agencies, commonly involved in these scenarios, are often pressured to find permanent placement for children, within an expedited timeframe, inconsistent with the need for sufficient time for recovery and goals of family inclusion and unity. We present the complicated case of a 25-year-old woman with a history of opioid use disorder and depression, who, after being in and out of treatment programs for years, had a lethal overdose. She had a significant family history of addiction and had lost custody of her children. This challenging, but common presentation draws attention to challenges in providing treatment during this opioid epidemic.
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 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".