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Record W2117111852 · doi:10.1002/dev.20473

Deficits in sensitivity to spacing after early visual deprivation in humans: A comparison of human faces, monkey faces, and houses

2010· article· en· W2117111852 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueDevelopmental Psychobiology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsHospital for Sick ChildrenMcMaster UniversityBrock University
FundersCanadian Institutes of Health Research
KeywordsPsychologyFeature (linguistics)Contrast (vision)Set (abstract data type)AudiologyCognitive psychologyArtificial intelligencePattern recognition (psychology)Computer scienceMedicine

Abstract

fetched live from OpenAlex

Abstract Early visual deprivation caused by bilateral congenital cataracts produces deficits in discriminating faces that differ in the spacing of features, but not in feature shape (Le Grand et al. [2001] Nature 410: 810). We investigated whether these deficits are specific to human faces by testing patients' ability to discriminate between stimuli differing only in feature spacing in human and monkey faces (Experiment 1) and in houses (Experiment 2). Patients, as a group, showed deficits on only one task: they had lower accuracy than normal in discriminating feature spacing in human faces. In contrast, they were normal in discriminating feature spacing in monkey faces and in houses. The results suggest that early visual experience is necessary to set up (or preserve) the neural architecture used for processing human faces, but not for processing objects in general. © 2010 Wiley Periodicals, Inc. Dev Psychobiol 52: 775–781, 2010.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.977

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 head0.052
GPT teacher head0.351
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