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Record W3105076415 · doi:10.1002/wcs.1549

Reframing spatial frames of reference: What can aging tell us about egocentric and allocentric navigation?

2020· review· en· W3105076415 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWiley Interdisciplinary Reviews Cognitive Science · 2020
Typereview
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsBaycrest HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsJames S. McDonnell Foundation
KeywordsCognitive reframingReference frameFrame of referencePsychologyCognitive psychologyComputer scienceFrame (networking)Social psychology

Abstract

fetched live from OpenAlex

Representations of space in mind are crucial for navigation, facilitating processes such as remembering landmark locations, understanding spatial relationships between objects, and integrating routes. A significant problem, however, is the lack of consensus on how these representations are encoded and stored in memory. Specifically, the nature of egocentric and allocentric frames of reference in human memory is widely debated. Yet, in recent investigations of the spatial domain across the lifespan, these distinctions in mnemonic spatial frames of reference have identified age-related impairments. In this review, we survey the ways in which different terms related to spatial representations in memory have been operationalized in past aging research and suggest a taxonomy to provide a common language for future investigations and theoretical discussion. This article is categorized under: Psychology > Memory Neuroscience > Cognition Psychology > Development and Aging.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0010.003
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.034
GPT teacher head0.342
Teacher spread0.308 · 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