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Record W2050236446 · doi:10.1027/1618-3169/a000061

Automatic Aspects in Face Perception

2010· article· en· W2050236446 on OpenAlex
David Anaki, Elena Irina Nica, Morris Moscovitch

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

VenueExperimental Psychology (formerly Zeitschrift für Experimentelle Psychologie) · 2010
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsBaycrest HospitalUniversity of Toronto
Fundersnot available
KeywordsPerceptionFace perceptionPsychologyCognitive psychologyCompatibility (geochemistry)Facial expressionCommunicationSocial psychologyNeuroscience

Abstract

fetched live from OpenAlex

We examined the perceptual dependency of local facial information on the whole facial context. In Experiment 1 participants matched a predetermined facial feature that appeared in two sequentially presented faces judging whether it is identical or not, while ignoring an irrelevant dimension in the faces. This irrelevant dimension was either (a) compatible or incompatible with the target's response and (b) same or different in either featural characteristics or metric distance between facial features in the two faces. A compatibility effect was observed for upright but not inverted faces, regardless of the type of change that differentiated between the faces in the irrelevant dimension. Even when the target was presented upright in the inverted faces, to attenuate perceptual load, no compatibility effect was found (Experiment 2). Finally, no compatibility effects were found for either upright or inverted houses (Experiment 3). These findings suggest that holistic face perception is mandatory.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.176
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0230.008

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 head0.054
GPT teacher head0.407
Teacher spread0.353 · 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