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Record W2027486410 · doi:10.1139/h11-053

Step-based translation of physical activity guidelines in the Lower Mississippi Delta

2011· article· en· W2027486410 on OpenAlexvenueno aff
Deirdre M. Harrington, Catrine Tudor‐Locke, Catherine M. Champagne, Stephanie T. Broyles, David W. Harsha, Betty M. Kennedy, William D. Johnson, H. Raymond Allen, Peter T. Katzmarzyk

Bibliographic record

VenueApplied Physiology Nutrition and Metabolism · 2011
Typearticle
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsnot available
Fundersnot available
KeywordsOverweightPhysical activityAccelerometerDeltaPopulationLinear regressionDemographyMedicinePhysical therapyStatisticsObesityMathematicsComputer scienceEnvironmental healthEngineeringInternal medicine

Abstract

fetched live from OpenAlex

To determine how many steps·day(-1) equate to current moderate-to-vigorous physical activity (MVPA) guidelines in a population from the Lower Mississippi Delta (LMD) of the United States, 58 overweight adults wore an Actigraph accelerometer (GT3X) for up to 2 weeks. Min·day(-1) in MVPA was a good predictor of steps·day(-1) (r(2) = 0.62; p < 0.001; linear regression), such that 30 min of daily MVPA equated to 9154 steps·day(-1) (mixed-model approach). Using receiver operating characteristic analysis, sensitivity and specificity were optimized at 8357 steps·day(-1). Results indicate that overweight residents of the LMD should be accumulating at least 8300-9100 steps·day(-1) to meet the recommendation of 30 min·day(-1) MVPA.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.259
Threshold uncertainty score0.515

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.087
GPT teacher head0.339
Teacher spread0.252 · 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

Citations6
Published2011
Admission routes1
Has abstractyes

Explore more

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