Determination of emotional endophenotypes: A validation of the Affective Neuroscience Personality Scales and further perspectives.
Bibliographic record
Abstract
The study of endophenotypes, notably with configured self-reports, represents a promising research pathway to overcome the limits of a syndromal approach of psychiatric diseases. The Affective Neuroscience Personality Scales (ANPS) is a self-report questionnaire, based on neuroethological considerations, that could help to assess emotional endophenotypes related to the activity in 6 core cerebral emotional systems (FEAR, ANGER, SADNESS, CARING, PLAYFULNESS, SEEKING). We further investigated its psychometric properties among 830 young adults and showed that they were satisfactory. As participants also completed several other self-reports that shared potential traits with the ANPS, we offer new validity evidence based on relations to other variables. We also provide additional evidence to consider that the ANPS scores can be validly interpreted for the characterization of emotional endophenotypes involved in a variety of psychiatric disorders. On the grounds of present results, of previous clinical studies, as well as some preliminary neuroimaging findings, we discuss new steps in the ANPS validation.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".