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Record W2078642016 · doi:10.3138/carto.44.3.159

fMRI and Human Subjects Research in Cartography

2009· article· en· W2078642016 on OpenAlexvenueno aff
Amy Lobben, Megan Lawrence, Judy M. Olson

Bibliographic record

VenueCartographica The International Journal for Geographic Information and Geovisualization · 2009
Typearticle
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsnot available
Fundersnot available
KeywordsFunctional magnetic resonance imagingCartographyPerceptionWindow (computing)Data scienceComputer sciencePsychologyGeographyNeuroscienceWorld Wide Web

Abstract

fetched live from OpenAlex

In the past decade, the use of functional magnetic resonance imaging (fMRI) has grown, both in the number of studies published and in the number of disciplines finding application for functional brain research facilitated by this data-gathering method. A review of fMRI research in perceptual grouping and figure/ground and in visual search and attention is of interest in the effort to understand the human use of maps. These studies provide physiological evidence that can at least tentatively be interpreted as supporting principles in map design. Although they are not specifically cartographic, these studies dovetail with some of the human-user research in cartography. The question of how these studies of very specific phenomena, using very limited graphics, fit the overall picture of map use is an open one. At the very least, they provide an additional window into the processes of map use.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.467

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
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 head0.024
GPT teacher head0.333
Teacher spread0.310 · 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 designTheoretical or conceptual
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

Citations15
Published2009
Admission routes1
Has abstractyes

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