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Record W1993439511 · doi:10.1068/i0406

Sensitivity to First- and Second-Order Drifting Gratings in 3-Month-Old Infants

2011· article· en· W1993439511 on OpenAlexaff
Vickie Armstrong, Daphne Maurer, Dave Ellemberg, Terri L. Lewis

Bibliographic record

Venuei-Perception · 2011
Typearticle
Languageen
FieldNeuroscience
TopicVisual perception and processing mechanisms
Canadian institutionsUniversité de MontréalMcMaster University
Fundersnot available
KeywordsFlickerSensitivity (control systems)OpticsModulation (music)Contrast (vision)Motion (physics)Motion perceptionPhysicsPerceptionOrientation (vector space)PsychologyMathematicsComputer scienceAcousticsNeuroscienceGeometry

Abstract

fetched live from OpenAlex

In two experiments, we investigated 3-month-old infants' sensitivity to first- and second-order drifting gratings. In Experiment 1 we used forced-choice preferential looking with drifting versus stationary gratings to estimate depth modulation thresholds for 3-month-old infants and a similar task for a comparison group of adults. Thresholds for infants were more adult-like for second-order than first-order gratings. In Experiment 2, 3-month-olds dishabituated to a change in first-order orientation, but not to a change in direction of first- or second-order motion. Hence, results from Experiment 1 were likely driven by the perception of flicker rather than motion. Thus, infants' sensitivity to uniform motion is slow to develop and appears to be driven initially by flicker-sensitive mechanisms. The underlying mechanisms have more mature tuning for second-order than for first-order information.

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)0.001
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.053
GPT teacher head0.295
Teacher spread0.242 · 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

Citations37
Published2011
Admission routes1
Has abstractyes

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