MétaCan
Menu
Back to cohort
Record W2052022788 · doi:10.1167/3.1.7

Change detection in an attended face depends on the expectation of the observer

2003· article· en· W2052022788 on OpenAlexafffund
Erin L. Austen, James T. Enns

Bibliographic record

VenueJournal of Vision · 2003
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeneralityObserver (physics)PsychologyPerceptionFacial expressionChange detectionFace (sociological concept)FlickerFace perceptionCognitive psychologySocial psychologyCommunicationComputer visionComputer scienceNeuroscienceSociology

Abstract

fetched live from OpenAlex

Sensitivity to a scene change during a brief interruption depends critically on a match between what the observer expects to see and the kind of change that occurs (Austen & Enns, 2000). The present study tested the generality of this conclusion using human faces, which are both socially more relevant and perceptually more configural than the compound letters tested previously. An experiment using the flicker technique examined sensitivity to two types of change: facial identity and emotional expression. Change detection was assessed when attention was either focused or distributed, the change was either expected or unexpected, and the faces were either upright or inverted. The main finding was that detection was expectation-dependent, even when only a single upright face was presented. Secondary findings with regard to attentional distribution and face inversion confirmed that observers were indeed engaged in face processing. We conclude that observer expectations critically influence the perception of single and fully attended human faces.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.407
Threshold uncertainty score0.130

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.137
GPT teacher head0.343
Teacher spread0.206 · 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 designBench or experimental
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

Citations36
Published2003
Admission routes2
Has abstractyes

Explore more

Same venueJournal of VisionSame topicFace Recognition and PerceptionFrench-language works237,207