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Record W2019714721 · doi:10.1167/9.14.71

Improved face discrimination after face adaptation

2009· article· en· W2019714721 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

VenueJournal of Vision · 2009
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsStimulus (psychology)PerceptionLuminanceAdaptation (eye)PsychologyFace perceptionFace (sociological concept)Cognitive psychologyVisual perceptionNeural adaptationCommunicationComputer scienceArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

Adaptation is a temporary change in the perception of visual stimuli caused by prior exposure to another stimulus. It has been observed in many stages and aspects of visual processing evidenced by perceptual-bias aftereffects as well as changes in sensitivity. Whether adaptation serves a functional purpose or it is merely a by-product of neural processing has remained an open question. For example, retinal light adaptation improves discrimination around the adapted luminance level. On the other hand, evidence has been mixed on various examples of cortical adaptation, such as contrast, orientation, motion. In this study we investigated whether a more recently discovered type of adaptation — face adaptation, acts as a beneficial process to improve face perception. We compared face discrimination thresholds across three adapting conditions: (1) same-face: where adapting and test faces were the same, (2) different-face: where adapting and test faces differed, and (3) baseline: where adapting stimulus was a blank.

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 score0.172
Threshold uncertainty score0.246

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 communication0.0000.001
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 head0.049
GPT teacher head0.352
Teacher spread0.303 · 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