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Record W2460624692 · doi:10.3138/cart.51.2.3129

Understanding Spatial Pattern Cognition from Tactile Maps and Graphics

2016· article· en· W2460624692 on OpenAlexvenueno aff
Nicholas A. Perdue, Amy Lobben

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2016
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsnot available
FundersNational Institutes of Health
KeywordsIdentification (biology)Cognitive mapSpatial cognitionCognitionObject (grammar)GraphicsReading (process)Spatial abilityPsychologyArtificial intelligenceComputer scienceCartographyCognitive psychologyGeographyBiologyEcologyNeuroscienceComputer graphics (images)

Abstract

fetched live from OpenAlex

This article explores the cognitive dimensions of spatial pattern identification in people who are blind or low vision using tactile graphics. We contend that spatial pattern identification is critical to the construction of an informative and rich environmental image, and insight into these cognitive skills can inform current practices in tactile map production and accessible cartography. This research investigates individual spatial thinking skills hypothesized to be components of spatial pattern identification. The findings suggest that Cartesian proximity and object differentiation are vital cognitive skills of spatial pattern identification and could potentially be exploited to communicate complex environmental knowledge in tactile reference maps. The relationship between prior map-reading training and test performance indicates a critical need for an increased presence of tactile cartographies and highlights future research opportunities.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.868
Threshold uncertainty score0.488

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.027
GPT teacher head0.250
Teacher spread0.223 · 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 designOther design
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

Citations7
Published2016
Admission routes1
Has abstractyes

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Same venueCartographica The International Journal for Geographic Information and GeovisualizationSame topicSpatial Cognition and NavigationFrench-language works237,207