Short‐Term Assessment of Risk and Treatability (START): the case for a new structured professional judgment scheme
Bibliographic record
Abstract
The Short-Term Assessment of Risk and Treatability (START) is a new structured professional judgment scheme intended to inform multiple risk domains relevant to everyday psychiatric clinical practice (e.g. risk to others, suicide, self-harm, self-neglect, substance abuse, unauthorized leave, and victimization). The article describes the processes involved in establishing an interdisciplinary approach to risk assessment and management. The authors present a review of the rationale for START, including the value of dynamic variables, the importance of strengths, and the extent to which clinicians must be attentive to multiple risk domains, reflecting theoretical and scientific evidence of the overlap among risks. Using the development, validation, and implementation of START as an example, the authors describe the processes by which other researchers, clinicians, and administrators could adapt existing assessment schemes or create new ones to bridge some remaining gaps in the risk assessment and management continuum.
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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 | 0.305 | 0.344 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.008 | 0.003 |
| Science and technology studies | 0.006 | 0.020 |
| Scholarly communication | 0.011 | 0.019 |
| Open science | 0.005 | 0.012 |
| Research integrity | 0.004 | 0.019 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".