Original Research Toward Benchmarks for Tertiary Care for Adults With Severe and Persistent Mental Disorders
Bibliographic record
Abstract
Background: Scarce attention has been paid to establishing benchmarks for tertiary care for adults with severe mental disorders. Yet, the availability and efficient utilization of resi-dential resources partly determines the capacity of a comprehensive system of care to avoid clogging ever-shrinking acute care bed facilities. Objectives: To describe the actual utilization of and projected needs for residential re-sources, one part of tertiary care, in the catchment area of a psychiatric hospital in east-end Montreal. To compare results obtained against actual utilization and projected needs evalu-ated in other Canadian provinces and in other countries, with a view to establishing na-tional benchmarks. Methods: Two surveys were undertaken to establish the number of places in these facili-ties that were utilized and needed for adults aged 18 to 65 years with severe mental disor-ders, without a primary diagnosis of mental retardation or organic brain syndrome, and originally from the catchment area. A first survey ascertained the number of places utilized and of those needed for residential care among all long-stay inpatients and all adults in supervised residential facilities. A second survey identified the need for such long-stay
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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 | 0.034 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".