Evidence‐based assessment as an integrative model for applying psychological science to guide the voyage of treatment.
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
Evidence-based assessment (EBA) streamlines literature reviewing and organizing clinical assessment by targeting the vital few topics, “satisficing,” and focusing on three major phases of clinical activity: prediction of diagnoses or other criteria, prescription of treatment or moderating factors, and process measurement. EBA is an organizing framework for applying a dozen steps to guide treatment. Technology is changing clinical assessment by increasing the efficiency and accuracy of scoring and feedback, as well as innovations that make more intensive assessment feasible. Fully implementing EBA suggests changes in training and requires a practice overhaul in exchange for greater efficiency, more accurate decisions, incrementally better outcomes, and increased service accessibility that could enable psychological science to help more people.
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 | 0.027 | 0.043 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.003 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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