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Record W2051067967 · doi:10.1167/7.12.5

Actual and illusory differences in constant speed influence the perception of animacy similarly

2007· article· en· W2051067967 on OpenAlexaff
Paul A. Szego, M. D. Rutherford

Bibliographic record

VenueJournal of Vision · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsMcMaster University
Fundersnot available
KeywordsAnimacyPerceptionPsychologyCognitive psychologyObject (grammar)Constant (computer programming)Robustness (evolution)CognitionSocial psychologyComputer scienceArtificial intelligence

Abstract

fetched live from OpenAlex

The ability to perceive objects as alive is the first step in social cognition. When the status of an object is ambiguous--if far away or fast moving--animacy is best perceived using motion cues. Previous studies have revealed that acceleration is a robust cue to animacy. The current study tests the prediction that, in the absence of acceleration, an object traveling at a relatively faster constant speed is more likely to be perceived as animate. Experiment 1 confirmed this hypothesis. Experiment 2 investigated the robustness of this finding by employing an illusory speed difference: Participants viewed dots moving at the same speed across apparently smaller and apparently larger central circles that were actually equally sized. Two thirds of participants perceived a dot traveling across an apparently larger circle to be faster or alive. Experiment 3 showed that participants' responses were not due to response bias. Together, these results suggest that our perceptions of animacy are influenced by constant speed differences, and that the perceptual association of speed and animacy is influenced by actual and illusory speed differences similarly.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.338
Threshold uncertainty score0.160

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.020
GPT teacher head0.319
Teacher spread0.299 · 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

Citations28
Published2007
Admission routes1
Has abstractyes

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