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Record W1890544775 · doi:10.1027/0044-3409/a000016

Non-Idiographic Emotional Script-Driven Imagery in Posttraumatic Stress Disorder

2010· article· en· W1890544775 on OpenAlexaff
Paul Frewen, Ruth A. Lanius

Bibliographic record

VenueZeitschrift für Psychologie / Journal of Psychology · 2010
Typearticle
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsWestern University
Fundersnot available
KeywordsPsychologyRecallNomothetic and idiographicEpisodic memoryAutobiographical memoryPriming (agriculture)Context (archaeology)Cognitive psychologyAnxietyMental imageTraumatic stressDevelopmental psychologyCognitionClinical psychologyNeuroscienceSocial psychology

Abstract

fetched live from OpenAlex

Abnormal emotional responses to standardized emotional stimuli in posttraumatic stress disorder (PTSD) implicate problems in emotional processing less obviously linked to traumatic experiences. However, the personal meaningfulness and association of standardized emotional stimuli with specific episodic memories in PTSD participants has not been investigated. This paper takes the position that emotional processing of standardized stimuli cannot be divorced from the personal meaning these stimuli are ascribed, such as via the priming of episodic memory. Women with PTSD reported greater priming of episodic memories within the context of emotional imagery of standardized scripts, and episodic recall predicted emotional responses to script-driven imagery. Furthermore, greater priming of episodic recall during imagery of fear-anxiety scripts was associated with less response within the ventral medial prefrontal cortex. Clinical, theoretical, and methodological issues are discussed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.052
GPT teacher head0.419
Teacher spread0.367 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2010
Admission routes1
Has abstractyes

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