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The Scars of Memory

2007· article· en· W2169994173 on OpenAlexafffund
Stephen Porter, Kristine A. Peace

Bibliographic record

VenuePsychological Science · 2007
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsDalhousie University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsPsychologyTraumatic memoriesConsistency (knowledge bases)Clinical psychologyInjury preventionPoison controlDevelopmental psychologyCognitive psychologyMedicineMedical emergency

Abstract

fetched live from OpenAlex

We conducted a prospective study with individuals who first described their memories of both a recent traumatic and a highly positive emotional experience in 2001-2002. Of the 49 subjects interviewed after 3 months, 29 were re-interviewed after 3.45 to 5.0 years. Subjects answered questions from a 12-item consistency questionnaire (maximum possible score of 36), rated the qualities of their memories, and completed questionnaires concerning the impact of the trauma. Results indicated that traumatic memories (including memories for violence) were highly consistent (M= 28.04) over time relative to positive memories (M= 17.75). Ratings of vividness, overall quality, and sensory components declined markedly for positive memories but remained virtually unchanged for traumatic memories. The severity of traumatic symptoms diminished over time and was unrelated to memory consistency. These findings contribute to understanding of the impact of trauma on memory over long periods.

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)0.001
metaresearch head score (Gemma)0.009
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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.044
GPT teacher head0.426
Teacher spread0.382 · 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

Citations114
Published2007
Admission routes2
Has abstractyes

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