MétaCan
Menu
Back to cohort
Record W2076124851 · doi:10.1037/a0025692

Determination of emotional endophenotypes: A validation of the Affective Neuroscience Personality Scales and further perspectives.

2011· article· en· W2076124851 on OpenAlexafffund
Jean‐Baptiste Pingault, Lydia Pouga, Julie Grèzes, Sylvie Berthoz

Bibliographic record

VenuePsychological Assessment · 2011
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsUniversité de MontréalResearch Unit on Children's Psychosocial Maladjustment
FundersEuropean CommissionGovernment of Canada
KeywordsEndophenotypePsychologyAngerSadnessPersonalityNeuroimagingBig Five personality traitsAffective neuroscienceClinical psychologyPsychometricsDevelopmental psychologyNeuroscienceCognitionSocial psychology

Abstract

fetched live from OpenAlex

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.

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.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.236
Threshold uncertainty score0.972

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.064
GPT teacher head0.373
Teacher spread0.309 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations32
Published2011
Admission routes2
Has abstractyes

Explore more

Same venuePsychological AssessmentSame topicPersonality Disorders and PsychopathologyFrench-language works237,207