CNS volume 13 supplement 6 Cover and Front matter
Bibliographic record
Abstract
Substance abuse and mental disorders commonly occur together and place an incalculable burden on individuals, families, and society at large. Left untreated, co-occurring psychiatric and substance use disorders may result in troubled and unproductive lives, as this comorbidity is associated with underachievement or failure at work and school, poor health, problems fulfilling family responsibilities, abuse, violence, and legal difficulties. Co-occurring disorders frequently have a complex and bidirectional relationship and may require longitudinal, repeated assessments to establish correct diagnosis. A number of reliable instruments have been developed to improve screening and assessment in both primary care and mental health settings, but controversy persists regarding the best approach to treatment. A fundamental issue, for example, is whether to treat a mood or an anxiety disorder in the presence of ongoing alcohol or drug abuse. Although recent recommendations suggest that concurrent substance abuse should not impede treatment of psychiatric symptoms, more evidence is required to facilitate decision making during acute treatment. Further, relapse and recurrence are common among individuals with co-occurring disorders, and the issue of long-term treatment typically needs to be addressed. Optimal patient management requires a collaborative effort by mental health care professionals, addiction specialists, and primary care physicians. Therefore, it is important that physicians who care for this patient population weigh the most recent evidence on effective and integrated treatment of individuals with co-occurring mood, anxiety, and alcohol use disorders.
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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.152 | 0.171 |
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; both teacher heads agree on what is shown here.
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".