RESEARCH ARTICLE The Burnaby treatment ce t u
Bibliographic record
Abstract
Full list of author information is available at the end of the articleBackground Individuals with concurrent mental and substance use disorders tend to present with multiple physical health problems and substantial social and behavioural prob-lems [1]. Individuals with concurrent disorders (CD) are overrepresented in forensic settings, regularly inhabit substandard housing [2,3] and constitute a significant percentage of the homeless population [4,5]. Individuals suffering from CD typically have difficulty engaging with traditional health care services and tend to rely heavily upon emergency care as their access point to the health care system [6]. The CD population exhibits extremely poor health outcomes and has a life expectancy that is considerably lower than the general population [7,8]. These and other concerns were recently emphasized by a group of leading American psychiatrists in a recent ‘call for action ’ [9]. In the Canadian province of British Columbia (BC), the highest numbers of patients with CD and those with the most severe problems are found within inner-city neighbourhoods. In Vancouver, the area known as the Downtown Eastside (DTES) has a particularly high con-centration of CD clients and has been the focus of con-siderable efforts to develop special treatment programs, including low threshold or harm reduction approaches
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.318 | 0.044 |
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".