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Record W2146972203 · doi:10.3389/fpsyg.2014.00732

How do episodic and semantic memory contribute to episodic foresight in young children?

2014· review· it· W2146972203 on OpenAlex
Gema Martín-Ordás, Cristina M. Atance, Julian S. Caza

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Psychology · 2014
Typereview
Languageit
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsChronesthesiaEpisodic memorySemantic memoryPsychologyReconstructive memoryFutures studiesAutobiographical memoryPerspective (graphical)Cognitive psychologyRetrospective memoryCognitive scienceTheory of mindChildhood memoryRecallCognitionNeuroscienceComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

Humans are able to transcend the present and mentally travel to another time, place, or perspective. Mentally projecting ourselves backwards (i.e., episodic memory) or forwards (i.e., episodic foresight) in time are crucial characteristics of the human memory system. Indeed, over the past few years, episodic memory has been argued to be involved both in our capacity to retrieve our personal past experiences and in our ability to imagine and foresee future scenarios. However, recent theory and findings suggest that semantic memory also plays a significant role in imagining future scenarios. We draw on Tulving's definition of episodic and semantic memory to provide a critical analysis of their role in episodic foresight tasks described in the developmental literature. We conclude by suggesting future directions of research that could further our understanding of how both episodic memory and semantic memory are intimately connected to episodic foresight.

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.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.687
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0070.001
Bibliometrics0.0040.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0020.000
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0010.001

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 head0.016
GPT teacher head0.318
Teacher spread0.302 · 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