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Record W2054214678 · doi:10.1080/15248370903453576

A Comparison of Preschoolers' Memory, Knowledge, and Anticipation of Events

2010· article· en· W2054214678 on OpenAlexaff
Elizabeth Quon, Cristina M. Atance

Bibliographic record

VenueJournal of Cognition and Development · 2010
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsEpisodic memoryPsychologyAnticipation (artificial intelligence)Semantic memoryMemory developmentAutobiographical memoryCognitive psychologyPerspective (graphical)Developmental psychologyChronesthesiaEvent (particle physics)CognitionCognitive developmentRecallArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

This study examined the development of the episodic and semantic memory systems, with an emphasis on the emergence of the two aspects of the former: episodic memory (the ability to re-experience a past event) and episodic future thinking (the ability to pre-experience a future event). Three-, 4-, and 5-year olds were randomly assigned to one of three conditions: past, semantic, or future. Children were asked questions about the same eight events, phrased in past, generalized present, or future tense. Half of these events were ones for which parents rated their children as having a high level of control (or input) over how the event unfolds, whereas the other half were rated as “low control.” Responses were scored with respect to their specificity and accuracy. Results revealed age differences in children's accuracy scores across all three conditions. Children's episodic future thinking and episodic memory, but not semantic memory, were less accurate for low-control events compared with high-control events. These results offer a new perspective on the development of the episodic and semantic memory systems and the methods used to assess them.

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)0.004
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 score0.011
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.044
GPT teacher head0.394
Teacher spread0.350 · 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

Citations54
Published2010
Admission routes1
Has abstractyes

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