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Record W1969356596 · doi:10.1371/journal.pone.0116910

Biological Motion Primes the Animate/Inanimate Distinction in Infancy

2015· article· en· W1969356596 on OpenAlexafffund
Diane Poulin‐Dubois, Cristina Crivello, Kristyn Wright

Bibliographic record

VenuePLoS ONE · 2015
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiological motionMotion (physics)AnimacySchematicCategorizationCommunicationCognitive psychologyPsychologyComputer scienceArtificial intelligenceEngineering

Abstract

fetched live from OpenAlex

Given that biological motion is both detected and preferred early in life, we tested the hypothesis that biological motion might be instrumental to infants' differentiation of animate and inanimate categories. Infants were primed with either point-light displays of realistic biological motion, random motion, or schematic biological motion of an unfamiliar shape. After being habituated to these displays, 12-month-old infants categorized animals and vehicles as well as furniture and vehicles with the sequential touching task. The findings indicated that infants primed with point-light displays of realistic biological motion showed better categorization of animates than those exposed to random or schematic biological motion. These results suggest that human biological motion might be one of the motion cues that provide the building blocks for infants' concept of animacy.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.026
Threshold uncertainty score0.940

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)0.0000.001

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 head0.113
GPT teacher head0.289
Teacher spread0.176 · 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.

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

Citations14
Published2015
Admission routes2
Has abstractyes

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