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Record W2470800567 · doi:10.6084/m9.figshare.20015455

Cognition and environment are predictors of infants' motor development over time

2022· dataset· en· W2470800567 on OpenAlexaboutno aff
Keila Ruttnig Guidony Pereira, Raquel Saccani, Nádia Cristina Valentini

Bibliographic record

VenueFigshare · 2022
Typedataset
Languageen
FieldMedicine
TopicInfant Development and Preterm Care
Canadian institutionsnot available
Fundersnot available
KeywordsCognitionPsychologyPhysical medicine and rehabilitationDevelopmental psychologyMedicineNeuroscience

Abstract

fetched live from OpenAlex

ABSTRACT We conducted a longitudinal investigation on the relationships among motor and cognitive development, biological aspects, maternal practices, parental knowledge, and family environments of infants. Forty-nine infants aged between 3 and 16 months participated in the study. They were evaluated through the Alberta Infant Motor Scale and the Cognitive Scale of the Bayley Scales of Infant Development. Their parents answered a questionnaire about biological factors, the Daily Activities of Infant Scale, affordances for motor development (Baby Scale) in the home environment, and the Brazilian version of the Knowledge of Infant Development Inventory. We conducted evaluations in schools for 4 months. Generalized estimating equations, Bonferroni correction, and Spearman's rank correlation coefficient were used. Significant associations were found in the (1) univariate analysis between motor and cognitive development and environmental factors (education level, income, toy availability, physical space, parental practices and knowledge, breastfeeding duration, and school frequency); (2) multivariate analyses between motor development and income, and between father's age and physical space at home. Motor and cognitive developments were concluded to depend on each other, and environmental factors were shown to be more significant in the associations rather than the biological ones, stressing the importance of home, of parental care, and of the experiences children go through along the first years of their lives.

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)0.008
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: Observational
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0110.003

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 head0.015
GPT teacher head0.222
Teacher spread0.207 · 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
GenreDataset

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

Citations5
Published2022
Admission routes1
Has abstractyes

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