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Record W2903411949 · doi:10.1371/journal.pone.0207800

Animacy cues facilitate 10-month-olds' categorization of novel objects with similar insides

2018· article· en· W2903411949 on OpenAlexafffund
Nina Anderson, Kristinn Meagher, Andrea N. Welder, Susan A. Graham

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersAlberta Children's Hospital FoundationNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsChildren's Hospital Foundation
KeywordsCategorizationAnimacyObject (grammar)PerceptionContrast (vision)PsychologyCognitive psychologyCommunicationComputer scienceArtificial intelligenceNeuroscience

Abstract

fetched live from OpenAlex

In this experiment, we examined whether sensitivity to the relevance of object insides for the categorization of animate objects is in place around 10 months of age. Using an object examining paradigm, 10-month-old infants' (N = 58) were familiarized to novel objects with varying outward appearances but shared insides in one of three groups: No cues, Eyes, and Cue control. During test trials, infants were presented with a novel in-category test object followed by an out-of-category test object. When objects were presented with animacy cues (i.e., Eyes), infants categorized the objects together. In contrast, when objects were presented without any added cues or when they were presented with a shared perceptual marker (Cue control, i.e., plastic spoons placed on top of the objects), infants showed no evidence of categorization. These results indicate that by 10 months of age, eyes signal to infants that objects share some kind of uniting commonality that may not be obvious or readily perceptually available.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score1.000

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)0.0010.000

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 head0.078
GPT teacher head0.264
Teacher spread0.186 · 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 teacher head, not a consensus.

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

Citations7
Published2018
Admission routes2
Has abstractyes

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