Psychiatric Management of Military- Related PTSD: Focus on Psychopharmacology
Bibliographic record
Abstract
et al., 1990et al., , Sareen et al., 2004)). Twelve month and lifetime prevalence rates of PTSD in the Canadian Regular Forces has been reported as 2.8% and 7.2% respectively (Statistics Canada, 2002).In Canadian veterans pensioned with a medical condition, the 1 month prevalence was 10.3% (Richardson et al., 2006).Other military samples have shown 6 month and lifetime prevalence rates of 11.6 and 20.0% respectively (O'Toole et al., 1996).The large variation in PTSD rates might be a function of the time elapsed between the end of a mission and the start of the mental health evaluation, the nature and frequency of potentially traumatic events within each mission and differences in measurement used i.e. self-report screening tools vs. diagnostic interview.Patients with PTSD often present first to their primary care clinician with mental health issues, (Del Piccolo et al., 1998) and as such demonstrate increased healthcare service use and costs (
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.003 |
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".