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Record W4389742310 · doi:10.3389/frym.2023.1239685

Keeping Your Joints Flexible Throughout Life

2023· article· en· W4389742310 on OpenAlex
Andreas Konrad, David G. Behm

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

VenueFrontiers for Young Minds · 2023
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsFlexibility (engineering)DeskVariety (cybernetics)Resistance (ecology)Training (meteorology)BusinessComputer scienceEngineeringGeographyMechanical engineeringEcologyBiologyArtificial intelligenceEconomicsMeteorology

Abstract

fetched live from OpenAlex

People are built to move. To survive, not so long ago, we had to search for food every day as hunters or gatherers. In modern times, however, our way of life has changed drastically. We can buy our food at the supermarket and many people can do their work at a desk. As a result, we move less and sit for several hours every day. This is called a sedentary lifestyle. Sedentary activities can lead to a dramatic decrease in flexibility in the joints. To overcome those challenges, we can do a variety of activities such as performing sports that require the full range of motion of our joints, as well as doing stretch training, foam rolling, or resistance training.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.050
Threshold uncertainty score0.634

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.056
GPT teacher head0.332
Teacher spread0.276 · 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