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Record W2014687205 · doi:10.1167/6.6.291

Temporal frequency matters: Sensitivity to second-order stimuli in 5-year-olds and adults

2010· article· en· W2014687205 on OpenAlexaff
Vickie Armstrong, T. L. Lewis, D. Maurer

Bibliographic record

VenueJournal of Vision · 2010
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsMcMaster University
Fundersnot available
KeywordsContrast (vision)GratingFlickerPsychologySensitivity (control systems)AudiologyTracking (education)Orientation (vector space)Spatial frequencyDevelopmental psychologyMathematicsOpticsComputer sciencePhysicsMedicine

Abstract

fetched live from OpenAlex

We compared 5-year-olds' and adults' sensitivity to moving second-order (SO) gratings in four combinations of temporal frequency (TF) and velocity (V). Contrast was modulated over trials to measure the minimum contrast modulation yielding 82% correct responses. Adults and 5-year-olds (n=64/ age grp) provided individual thresholds for one of the four TFxV conditions (TF = 6Hz and V = 6 or 1.5 d/s; TF = 0.75Hz and V = 6 or 3 d/s) and for two tasks (direction discrimination and discrimination of a moving from a simultaneously presented static grating). Five-year-olds had higher thresholds than adults for all TFxV conditions, especially when TF = 0.75Hz. Control studies with an orientation discrimination task indicate that 5-year-olds' higher thresholds cannot be explained solely by poorer sensitivity to the patterns. When TF = 6Hz, but not when TF = 0.75 Hz, participants at both ages were more sensitive to SO information when the task was to discriminate a moving from a static grating than when it was to discriminate direction. Based on Seiffert and Cavanaugh (1998), it is likely that when TF is 6 Hz, participants use position-tracking mechanisms to discriminate direction and they use flicker-sensitive mechanisms to discriminate a moving from a static grating. At lower TFs, they likely use position-tracking mechanisms for both tasks (Seiffert & Cavanaugh,1998). Thus, the differential immaturities evident in the results likely reflect different rates of development for these underlying mechanisms.

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)0.001
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.026
GPT teacher head0.334
Teacher spread0.308 · 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

Citations0
Published2010
Admission routes1
Has abstractyes

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