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Record W2767356912 · doi:10.1177/0276236617739398

Examining Children’s Physical Activity, Imagery Ability, and Active Play Imagery

2017· article· en· W2767356912 on OpenAlex
Michelle Guerrero, Krista J. Munroe‐Chandler

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueImagination Cognition and Personality · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsMental imagePsychologyPhysical activityMultilevel modelMovement (music)Developmental psychologyCognitionComputer sciencePhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

The purpose of the present study was to determine whether physical activity participation and movement imagery ability predicted the three types of active play imagery (i.e., capability, social, and fun). A total of 120 children ( M age = 9.94 years, SD = .81) completed the Physical Activity Questionnaire for Older Children, Movement Imagery Questionnaire for Children, and Children’s Active Play Imagery Questionnaire. Hierarchical regression analyses revealed that age (control variable) and physical activity participation were positive predictors of capability, social, and fun imagery. External visual imagery positively predicted fun imagery, while no other associations between movement imagery ability and active play imagery were found. These results suggest that active play imagery is influenced by one’s age, physical activity participation, and ability to use external visual imagery.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.748
Threshold uncertainty score0.954

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.050
GPT teacher head0.349
Teacher spread0.298 · 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