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Record W2911391632 · doi:10.1016/s2214-109x(18)30512-6

Accuracy and inequalities in physical activity research

2019· letter· en· W2911391632 on OpenAlexaffabout
Jean‐Philippe Chaput

Bibliographic record

VenueThe Lancet Global Health · 2019
Typeletter
Languageen
FieldMedicine
TopicPhysical Activity and Health
Canadian institutionsAgricultural Research Institute of OntarioUniversity of Ottawa
Fundersnot available
KeywordsScopusPublic healthScale (ratio)Physical activityPopulationQuarter (Canadian coin)PsychologyGerontologyMEDLINEMedicineEnvironmental healthPolitical scienceGeographyCartographyPhysical therapy

Abstract

fetched live from OpenAlex

In their Article on global estimates and trends of insufficient physical activity in adults, Regina Guthold and colleagues (October, 2018)1 included data from nearly 2 million participants who were representative of 96% of the global population. A key finding was that about a quarter (27·5%) of adults worldwide do not get enough physical activity to meet current public health guidelines. However, this estimate was based on self-reported questionnaires and probably misrepresents the true burden of physical inactivity around the world.

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)0.277
metaresearch head score (Gemma)0.681
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.723
Threshold uncertainty score0.891

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.2770.681
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.003
Bibliometrics0.0140.016
Science and technology studies0.0030.010
Scholarly communication0.0140.016
Open science0.0040.012
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0070.002

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 head0.299
GPT teacher head0.518
Teacher spread0.219 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designTheoretical or conceptual
DomainMethods
GenreCommentary

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
Published2019
Admission routes2
Has abstractyes

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