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Record W2530427207 · doi:10.1037/xap0000103

Where are you? The effect of uncertainty and its visual representation on location judgments in GPS-like displays.

2016· article· en· W2530427207 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

VenueJournal of Experimental Psychology Applied · 2016
Typearticle
Languageen
FieldDecision Sciences
TopicDecision-Making and Behavioral Economics
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGlyph (data visualization)VisualizationComputer scienceGlobal Positioning SystemTask (project management)Consistency (knowledge bases)Representation (politics)Artificial intelligenceFunction (biology)Data miningStatisticsMathematics

Abstract

fetched live from OpenAlex

Two experiments revealed how nonexperts interpret visualizations of positional uncertainty on GPS-like displays and how the visual representation of uncertainty affects their judgments. Participants were shown maps with representations of their current location; locational uncertainty was visualized as either a circle (confidence interval) or a faded glyph (indicating the probability density function directly). When shown a single circle or faded glyph, participants assumed they were located at the center of the uncertain region. In a task that required combining 2 uncertain estimates of their location, the most common strategy-integration-was to take both estimates into account, with more weight given to the more certain estimate. Participants' strategies were not affected by how uncertainty was visualized, but visualization affected the consistency of responses, both within individuals and in relation to models of individual's preferred strategies. The results indicate that nonexperts have an intuitive understanding of uncertainty. Rather than arguing for a particular method of visualizing uncertainty, the data suggest that the best visualization method is task dependent. (PsycINFO Database Record

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)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.387
Threshold uncertainty score0.268

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.074
GPT teacher head0.455
Teacher spread0.381 · 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