Bibliographic record
Abstract
Few things in life afford more pleasure than that of a job well done. Medical professionals know this and are com-mitted to offering patients high-quality service, genuine caring, respect, personal integrity and ethical conduct. This requires not only skill and dedication but also up-to-date knowledge of the field, sound judgment and reasonable strength of character. As never before, modern psychiatrists must be able to keep abreast of new scientific information, of changes in societal values and expectations, and of constantly evolving patterns of standards and practice. No longer are patients willing to accept a passive role with regard to their medical care. Enhanced access to information and the increasing emphasis on shared responsibility and physician accountability have created new challenges for patients and caregivers alike. We as psychiatrists can respond to these challenges by developing practice standards based on the latest scientific evi-dence and by stimulating meaningful discussion of important issues among experienced practitioners. The Bulletin will be publishing articles related to professional standards and ethics on a regular basis throughout the year—articles that will be timely, relevant and practical. Some will reflect current best practice, others will offer informed opinion, and some, we hope, will stimulate lively discussion and debate. We look forward to your responses, contributions and crea-tive ideas to make this section interesting, thought-provoking and clinically useful. The first article in this series has been provided by Dr. Joel Paris, Professor and Chair of Psychiatry at McGill Univer-sity. Dr. Paris was a proponent of evidence-based medicine long before it became fashionable. He discusses aspects of evidence-based medicine that apply specifically to psychiatry. We hope that you will enjoy reading his paper and that you will reply with some of your own views and opinions. Evidence-Based Psychiatry:
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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 | 0.025 | 0.096 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.009 | 0.048 |
| Scholarly communication | 0.021 | 0.031 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.011 | 0.035 |
| Insufficient payload (model declined to judge) | 0.011 | 0.008 |
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".