Bibliographic record
Abstract
OBJECTIVE: The purpose of this communication is to alert psychiatrists to the difficulties of translating results of group difference obtained from large, randomized clinical trials to the treatment of individual patients. METHOD: Reported discrepancies between a) clinical trial participants and general psychiatric patients, b) clinical trial investigators and general clinicians, and c) study trial and usual clinic conditions were assessed. RESULTS: The results confirm that important differences exist in all 3 areas. CONCLUSIONS: Recommendations for researchers include more complete assessments of factors that account for individual difference, an appraisal of outcomes more important to patients than symptom scores, and the use of statistical methods that permit the evaluation of individual difference. Recommendations for clinicians include a careful differentiation of results obtained in different phases of clinical trials and a clear appreciation of the different purposes of those trials. Clinicians should also appreciate that short-term effectiveness is not the same as long-term outcome and that aggregate scores may not apply to individual patients.
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 | 0.816 | 0.955 |
| Meta-epidemiology (narrow) | 0.004 | 0.005 |
| Meta-epidemiology (broad) | 0.016 | 0.006 |
| Bibliometrics | 0.013 | 0.021 |
| Science and technology studies | 0.006 | 0.044 |
| Scholarly communication | 0.042 | 0.033 |
| Open science | 0.011 | 0.010 |
| Research integrity | 0.039 | 0.028 |
| Insufficient payload (model declined to judge) | 0.008 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".