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Infants' Reactions to Object Collision on Hit and Miss Trajectories

2007· article· en· W1973028836 on OpenAlexafffund
Mark A. Schmuckler, Lisa M. Collimore, James L. Dannemiller

Bibliographic record

VenueInfancy · 2007
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsInstitute for Christian Studies
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsLoomingObject (grammar)PsychologyPerceptionContext (archaeology)CollisionPath (computing)SightCognitive psychologyComputer visionArtificial intelligenceCommunicationComputer scienceComputer securityPhysicsNeuroscience

Abstract

fetched live from OpenAlex

This experiment investigated the impact of the path of approach of an object, from head on versus from the side, and the type of imminent contact with that object, a hit versus a miss, on young infants' perceptions of object looming. Consistent with earlier studies, we found that 4- to 5-month-old infants do indeed discriminate hits versus misses. We also found a novel result regarding the path of the approaching object. The discrimination of hits from misses was modified by whether or not the approaching objects passed in front of the infants' faces; objects crossing the line of sight evoked more frequent defensive reactions than objects that did not cross the line of sight, regardless of whether or not such objects were on a collision course. These findings are discussed within the context of the development of visually guided locomotion and linear versus nonlinear paths of translation through the world.

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)0.009
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.317
Teacher spread0.301 · 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

Citations24
Published2007
Admission routes2
Has abstractyes

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