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Record W2069218205 · doi:10.1167/9.12.18

Preservation of shape discrimination in aging

2009· article· en· W2069218205 on OpenAlexaff
Claudine Habak, F. Wilkinson, Hugh R. Wilson

Bibliographic record

VenueJournal of Vision · 2009
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsYork University
Fundersnot available
KeywordsRepresentation (politics)LuminanceTexture (cosmology)Function (biology)Shape analysis (program analysis)Object (grammar)NeuroscienceArtificial intelligenceComputer sciencePsychologyBiologyImage (mathematics)Evolutionary biology

Abstract

fetched live from OpenAlex

The representation of objects becomes increasingly complex at higher levels of the human visual cortex. Shapes of intermediate complexity serve as a step in the representation of such intricate constructs. Healthy aging has adverse effects on cortical function, and we sought to determine the effects of age on the efficacy and speed of neuronal mechanisms underlying shape processing. Using deformed circular shapes, we probe object representation by varying the characteristics that define the shape and by assessing lateral interactions among shapes. Results indicate that performance declines with age for shapes defined by texture but not by luminance. However, there is no age-related slowing for the processing of shape, and probes of lateral interactions reveal spared function for complex shape combinations. Findings suggest that the effect of age on shapes defined by texture arises from lower stages of visual processing, and that the representation of shape combinations is spared because of its robust nature.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.076
GPT teacher head0.387
Teacher spread0.311 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations28
Published2009
Admission routes1
Has abstractyes

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