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Record W2151978331 · doi:10.1037/a0033776

Connecting spatial memories of two nested spaces.

2013· article· en· W2151978331 on OpenAlexafffundabout
Hui Zhang, Weimin Mou, Timothy P. McNamara, Lin Wang

Bibliographic record

VenueJournal of Experimental Psychology Learning Memory and Cognition · 2013
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsUniversity of Alberta
FundersNational Institute of Mental HealthNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsHeading (navigation)Bearing (navigation)BeijingComputer scienceTable (database)Point (geometry)Cardinal directionArtificial intelligenceCartographyGeographyInformation retrievalMathematicsGeodesyGeometryData mining

Abstract

fetched live from OpenAlex

Four experiments investigated the manner in which people use spatial reference directions to organize spatial memories of 2 conceptually nested layouts. Participants learned directions of 8 remote cities centered to Beijing or Edmonton, where the experiments occurred, using a map or using direct pointing. The map and the environment were aligned, and participants faced north (0°). Participants also learned locations of 7 objects on a table. Participants faced north (0°) during learning but were instructed to learn the layout along the northwest-southeast (45°-225°) axis. Judgments of relative direction (imagine you are standing at X, facing Y, point to Z) were used to determine spatial reference directions in retrieval of bearings between 2 objects or 2 cities. The results showed that when the tested bearing and the imagined heading were within an array, participants used 0° as the reference direction in retrieving bearings between cities but used 45°-225° to retrieve bearings between objects. When the tested bearing and the imagined heading were across 2 arrays, participants used the reference direction of the array from which the tested bearing was. These results indicated that bearings between items within an array were represented only with respect to the reference directions of this array and the relationship between spatial reference directions in these 2 arrays was also represented.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.036
Threshold uncertainty score0.535

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.016
GPT teacher head0.296
Teacher spread0.280 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations12
Published2013
Admission routes3
Has abstractyes

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