How Affective Science Can Inform Clinical Science
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 construct of emotion dysregulation has been used to describe and explain diverse psychopathologies. Although this is intuitively appealing and sensible, the application of emotion reactivity and regulation to the study of psychopathology has, to a large extent, proceeded independently from concepts and measures informed by affective science. Utilizing the innovative research approaches, measures, paradigms, and insights that have emerged in the burgeoning field of affective science holds substantial promise for emotion dysregulation theories of psychopathology. In this introduction to the special series on emotions and psychopathology, we review many of these advances, and highlight several broad methodological and conceptual issues that researchers seeking to continue this crosscutting work should bear in mind. We close with a brief review of the six articles that constitute the special series, noting how each exemplifies the pioneering methodological and substantive advances that are typical of the best work in this new interdisciplinary field.
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 | 0.062 | 0.040 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.007 |
| Science and technology studies | 0.002 | 0.075 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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