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Record W6990229582

Deconstructing visual-spatial cognition in typically developing children

2009· dissertation· en· W6990229582 on OpenAlexaff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2009
Typedissertation
Languageen
FieldEngineering
TopicSpatial Cognition and Navigation
Canadian institutionsMcGill University
Fundersnot available
KeywordsMental rotationCognitionTypically developingMental ageTask (project management)Cognitive developmentElementary cognitive taskMental representation
DOInot available

Abstract

fetched live from OpenAlex

Visual-spatial cognition was examined in typically developing children. Fifty-six children between 3- to 10-years-old completed a comprehensive battery of cognitive tasks that tapped 8 components of visual-spatial functioning. Results demonstrate that task complexity and age interact across the majority of visual-spatial sub-domains, with visual-spatial competencies increasing linearly with age. Examination of acquisition rates showed that after 8 years of age children are capable of performing each measure significantly better than chance. Gender-age-related findings suggest males demonstrate superior visual-spatial mental rotation skills only until 9-10 years of age, than females begin to surpass males. Visual-spatial cognition and mathematical performance was also investigated in typical children. Children's visual-spatial mental rotation and manipulation and visual-spatial directionality abilities were positively correlated with mathematical performance.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.973
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.238
Teacher spread0.228 · 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 designOther design
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

Citations0
Published2009
Admission routes1
Has abstractyes

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