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Record W4246663395 · doi:10.31234/osf.io/qr4f9

Individual Differences in Autobiographical Memory

2018· preprint· en· W4246663395 on OpenAlexaff
Daniela J. Palombo, Signy Sheldon, Brian Levine

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsAutobiographical memoryMnemonicRecallPsychologyCognitive psychologyEpisodic memoryChildhood memoryDevelopmental psychologyCognitionNeuroscience

Abstract

fetched live from OpenAlex

Although humans have a remarkable capacity to recall a wealth of detail from the past, there are marked inter-individual differences in the quantity and quality of our mnemonic experiences. Such differences in autobiographical memory may appear self-evident, yet there has been little research on this topic. In this review, we synthesize an emerging body of research regarding individual differences in autobiographical memory. We focus on two syndromes that fall at the extreme of the ‘remembering’ dimension, Highly Superior Autobiographical Memory (HSAM) and Severely Deficient Autobiographical Memory (SDAM). We also discuss findings from research on less extreme individual differences in autobiographical memory. This avenue of research is pivotal for a full description of the behavioral and neural substrates of autobiographical memory.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.128
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0140.001

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 head0.061
GPT teacher head0.339
Teacher spread0.278 · 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; both teacher heads agree on what is shown here.

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

Citations14
Published2018
Admission routes1
Has abstractyes

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