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Record W4390914113 · doi:10.23923/pap.psicol.3030

Memory wars: A solution to the conflict

2024· article· en· W4390914113 on OpenAlexaff
Claudia Morales, Antonio L. Manzanero

Bibliographic record

VenuePapeles del Psicólogo - Psychologist Papers · 2024
Typearticle
Languageen
FieldNeuroscience
TopicMemory Processes and Influences
Canadian institutionsWestern University
FundersUniversidad Complutense de Madrid
KeywordsPolitical scienceComputer science

Abstract

fetched live from OpenAlex

The validity of dissociative memory in forensic contexts and the causes of the so-called "memory wars" are discussed. Misconceptions between clinical and forensic psychology, a deficient definition of amnesia, and the difficulties inherent in studying traumatic memories contribute to the persistence of this controversy. Particularly in the field of forensic psychology, the debate could be attributed to the lack of consensus on scientific evidence. Psychologists need to establish an empirical foundation to understand better the mechanisms of memory involved in remembering and forgetting traumatic memories. The Continuous Accessibility Model of Memory is outlined to explain the retrieval of the different degrees of accessibility to autobiographical memories based on different factors.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.848
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.003

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 head0.081
GPT teacher head0.346
Teacher spread0.265 · 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.

Study designNot applicable
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

Citations6
Published2024
Admission routes1
Has abstractyes

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