Evidence-Based Practice in the Evaluation and Treatment of Sexual Offenders
Bibliographic record
Abstract
This editorial addresses evidence based medical practice in forensic psychiatry and particularly in the field of paraphilia. John M. Bradford is a Professor in the Department of Psychiatry and Behavioural Neurosciences, McMaster University. He is an Emeritus Professor at the University of Ottawa where he was a founder of the Royal Ottawa Institute of Mental Health Research. He is a Founder of Forensic Psychiatry, granted by the Royal College of Physicians and Surgeons of Canada. Abdullah H Alqahtani is an Assistant Professor and Consultant Psychiatrist at King Fahd University Hospital, Imam Abdulrahman Bin Faisal University, Dammam, Saudi Arabia. He is currently completing a clinical fellowship in forensic psychiatry at McMaster University - St. Joseph’s Healthcare Hamilton. Andrew T. Olagunju is an academic psychiatrist with a Senior Lecturer position at the College of Medicine, University of Lagos, Nigeria. He is also completing a clinical fellowship at McMaster University - St. Joseph’s Healthcare Hamilton.
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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 | 0.094 | 0.356 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.008 | 0.004 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.006 | 0.007 |
| Research integrity | 0.010 | 0.011 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".