Introduction to the special section on developing guidelines for the evidence-based assessment (EBA) of adult disorders.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The goal of this special section is to encourage greater awareness of evidence-based assessment (EBA) in the development of a scientifically supported clinical psychology. In this introductory article, the authors describe the elements that authors in this special section were asked to consider in their focused reviews (including the scope of available psychometric evidence, advancements in psychopathology research, and evidence of attention to factors such as gender, age, and ethnicity in measure validation). The authors then present central issues evident in the articles that deal with anxiety, depression, personality disorders, and couple distress and in the accompanying commentaries. The authors conclude by presenting key themes emerging from the articles in this special section, including gaps in psychometric information, limited information about the utility of assessment, the discrepancy between recommended EBAs and current training and practice, and the need for further data on the process of clinical assessment.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it