Assessment of Neuropsychological Functioning
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
Abstract Neuropsychology, like most other subspecialties in psychology, has undergone extensive and rapid changes and development over the past few decades. This has been particularly the case for neuropsychology within the past several years, as the 1990s were designated as the decade of the brain. Neuropsychology has been shaped by both economic pressures and changes and technological developments. These alterations in the field have lead to the development of new clinical avenues, technological progress, clinical and theoretical breakthroughs, and fundamental changes in the practice and teaching of neuropsychology. This chapter will explore these changes and developments focusing on both clinical and experimental areas, as well as offer some insight and advice regarding how these changes are affecting the field today. The chapter starts with a brief historical perspective, and then discusses the exciting and popular new clinical areas of sports‐related concussion and forensic neuropsychology. This is followed by a discussion of recent developments and issues in neuropsychological assessment and how advances in psychometric properties have improved neuropsychological assessment techniques. The final section discusses recent advances in experimental neuropsychology, mainly its role in fMRI research and transcranial magnetic stimulation, followed by an overview and ideas about the future direction of neuropsychology.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.027 | 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