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Record W6925098697 · doi:10.17605/osf.io/ev4zx

The Impact of Event Similarity on Recalls of Repeated Events

2022· other· en· W6925098697 on OpenAlex

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

VenueOSF Preprints (OSF Preprints) · 2022
Typeother
Languageen
FieldMedicine
TopicNutrition and Health Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRecallEpisodic memoryRepeated measures designEvent (particle physics)Semantic memorySimilarity (geometry)Long-term memoryAutobiographical memory

Abstract

fetched live from OpenAlex

Psychologists are becoming increasingly interested in studying memories for repeated events as a bridge between 'episodic' memory (i.e., memory for specific events localized in time and place) and 'semantic' memory (i.e., memory for general facts and information). However, the relative contribution of episodic and semantic memory in recalls of repeated events has yet to be determined: do repeated events rely more on episodic memory or semantic memory? Moreover, do different repeated events utilize these forms of memory to different degrees? Prior experimental research has shown that children are more accurate in their recall of specific episodes of repeated events when the repeated events are low in similarity. Conversely, when episodes of repeated events are high in similarity, children tend to recall more details about the 'gist' of the event or, in other words, the details that are fixed across episodes (Danby et al., 2019). Do recalls of repeated events in adults follow a similar pattern, such that repeated events lower in similarity utilize more episodic memory and repeated events high in similarity utilize more semantic memory? Here, the “similarity” of an event refers to a continuum from low-similarity (where each episode of a repeated event is very different) to high-similarity (where each episode of a repeated event is very similar). Danby, M. C., Sharman, S. J., Brubacher, S. P., & Powell, M. B. (2019). The effects of episode similarity on children’s reports of a repeated event. Memory, 27(4), 561–567. https://doi.org/10.1080/09658211.2018.1529798.

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)0.003
metaresearch head score (Gemma)0.002
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.553
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.5960.043

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 head0.028
GPT teacher head0.351
Teacher spread0.323 · 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