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Record W1996763207 · doi:10.1002/dev.20214

Infants' visual‐proprioceptive intermodal perception with imperfect contingency information

2007· article· en· W1996763207 on OpenAlexaff
Mark A. Schmuckler, DERRYN JEWELL

Bibliographic record

VenueDevelopmental Psychobiology · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
Fundersnot available
KeywordsContingencyPsychologyPerceptionCognitive psychologyContext (archaeology)Perfect informationImperfectMovement (music)CommunicationSpatial contextual awarenessArtificial intelligenceComputer scienceNeuroscienceGeographyMathematics

Abstract

fetched live from OpenAlex

Two experiments explored 5-month-old infants' recognition of self-movement in the context of imperfect contingencies between felt and seen movement. Previous work has shown that infants can discriminate a display of another child's movements from an on-line video display of their own movements, even when featural information is removed. These earlier findings were extended by demonstrating self versus other discrimination when the visual information for movement was an unrelated object (a fluorescent mobile) directly attached to the child's leg, thus producing imperfect spatial and temporal contingency information. In contrast, intermodal recognition failed when the mobile was indirectly attached to infants' legs, thus eliminating spatial contingencies altogether and further weakening temporal contingencies. Together, these studies reveal that even imperfect contingency information can drive intermodal perception, given appropriate levels of spatial and temporal contingency 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 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.416
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0030.003

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 head0.007
GPT teacher head0.284
Teacher spread0.277 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2007
Admission routes1
Has abstractyes

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