[Activity to prevent mental diseases after the Great East Japan Earthquake].
Bibliographic record
Abstract
Following the Great East Japan Earthquake, we have been supporting psychiatric hospitals and mental health and welfare centers in Miyagi Prefecture. In October 2011, with a grant from Miyagi Prefecture, the Department of Preventive Psychiatry was established in Tohoku University Graduate School of Medicine. The institute aims to promote the prevention of and early intervention for mental diseases. As its members, we carry out our duties in collaboration with the Miyagi Disaster Mental Health Care Center. We refer to our activities as the Great East Japan Earthquake Mental Health Support and Research (GEMS) project. The GEMS project includes both practices and research in the affected areas in Miyagi Prefecture. The focus is on supporting those who provide services for survivors long-term, such as municipal employees, nurses, fire fighters, and staff of the social welfare council. We investigated how much the disaster impaired the functioning of psychiatric hospitals and clinics in Miyagi Prefecture. We also conduct mental health surveys in public organizations. Based on the results, we arrange workshops, consultation, or counseling. Moreover, we promote improvement of the mental health skills of mental health professionals, which are essential for mid and long-term support after the disaster. One of them is "Skills for Psychological Recovery". As members of the support organization in the region, we keep working toward the recovery and development of mental health systems in Miyagi Prefecture.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.021 | 0.005 |
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".