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Record W2059205125 · doi:10.1068/p6396

Effects of Familiarity on Spatial Frequency Thresholds for Face Matching

2009· article· en· W2059205125 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

VenuePerception · 2009
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsOctave (electronics)PsychologyMatching (statistics)Face (sociological concept)Face perceptionSpatial frequencyPerceptionMathematicsAcousticsStatisticsOpticsPhysicsLinguistics

Abstract

fetched live from OpenAlex

We examined whether familiarity with a face influences the spatial frequencies (SFs) required for face matching. Using the psychophysical method of constant stimuli and a 3AFC simultaneous matching paradigm, we obtained SF thresholds for familiar- and unfamiliar-face matching from fourteen observers, of which four were personally familiar with a subset of the faces while the remainder served as controls. SF thresholds from the lower extreme of the spectrum were approximately one octave lower for familiar than for unfamiliar faces, while SF thresholds from the upper extreme of the spectrum were approximately a third of an octave higher. These results highlight a quantitative difference between processing familiar and unfamiliar 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.

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 score0.458
Threshold uncertainty score0.459

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 head0.032
GPT teacher head0.302
Teacher spread0.270 · 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