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Record W1978845746 · doi:10.2174/1874350101003010091

On the Interaction Between Stimulus Features and Context in the Perception of Causality

2010· article· en· W1978845746 on OpenAlexafffund
Jonathan A. Fugelsang, Matthew E. Roser

Bibliographic record

VenueThe Open Psychology Journal · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPerceptionStimulus (psychology)PsychologyCognitive psychologyCausality (physics)AttributionPerceptual systemVisual perceptionSocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

Much research has supported the hypothesis that the perceptual system generates impressions of causality based on simple cues available in the environment. We review evidence that this extraction of causal relations from perceptual cues is likely an automatic property of the visual system akin to other basic perceptual processes, such as perceptual grouping and illusory contour completion. We posit that it is this automatic characteristic of perceptual causality that underlies the proliferation of context effects associated with perceived causal events. Here, the presence of a perceived causal relationship may impact the perception of other features of the causal stimulus and other stimuli surrounding the causal event. We discuss current research, and present future research directions that promise to uncover some of the mechanisms underlying how causality is attributed from, and changes how we perceive and respond to, simple low-level stimuli in the environment. Such research will enrich our understanding of how the perception of causally-relevant stimulus features interacts with their context to enable us to effectively perceive, understand, and act upon our environment.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.805
Threshold uncertainty score0.615

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 science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.140
GPT teacher head0.455
Teacher spread0.315 · 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 designObservational
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

Citations0
Published2010
Admission routes2
Has abstractyes

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