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Record W2339271447 · doi:10.1139/apnm-2016-0023

The relationship between physical activity level and cardiovascular disease biomarkers in healthy, normal-weight 3- to 6-year-old children and their parents

2016· article· en· W2339271447 on OpenAlexafffundvenue
Carol Huang, Marja Cantell, Susan Crawford, Deborah Dewey, Danièle Pacaud

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2016
Typearticle
Languageen
FieldMedicine
TopicObesity, Physical Activity, Diet
Canadian institutionsAlberta Children's HospitalUniversity of Calgary
FundersAlberta Health Services
KeywordsAdiponectinMedicinePhysical activityTriglycerideProspective cohort studyDiseaseInsulin sensitivityInternal medicinePopulationBiomarkerLongitudinal studyCorrelationObesityEndocrinologyGerontologyPhysical therapyInsulin resistanceEnvironmental healthBiologyCholesterolPathology

Abstract

fetched live from OpenAlex

To determine if physical activity is linked to cardiovascular biomarkers in preschool children at risk, we need information on these biomarkers in healthy normal-weight children. In this population, multi-level modelling analyses found no correlation between accelerometer recorded physical activity and fasting lipids, adiponectin, or insulin sensitivity. Exploratory analyses found positive correlations between adiponectin and time spent in light physical activity, and between triglyceride and time spent in sedentary behaviour; these findings need to be confirmed in longitudinal prospective studies.

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)0.002
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
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 science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.027
GPT teacher head0.269
Teacher spread0.242 · 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

Citations2
Published2016
Admission routes3
Has abstractyes

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