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Record W4399547596 · doi:10.1183/20734735.0180-2023

Unravelling the complex interplay of factors behind exercise limitations and physical inactivity in COPD

2024· article· en· W4399547596 on OpenAlexaff
Clarice Tang, Bruce Bernstein, Felicity Blackstock, Astrid Blondeel, Andrea S. Gershon, Elena Gimeno‐Santos, Rainer Gloeckl, Alda Marques, Martijn A. Spruit, Chris Garvey, Mike Morgan, Linda Nici, Sally Singh, Thierry Troosters

Bibliographic record

VenueBreathe · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Obstructive Pulmonary Disease (COPD) Research
Canadian institutionsHealth Sciences CentreUniversity of TorontoSunnybrook Health Science Centre
Fundersnot available
KeywordsCOPDPhysical activitySedentary lifestylePulmonary rehabilitationMedicinePhysical therapyRehabilitationSedentary behaviorHealth benefitsPsychologyPhysical medicine and rehabilitationPsychiatry

Abstract

fetched live from OpenAlex

Exercise limitation and physical inactivity are known treatable traits for people with COPD. Maximising exercise capacity and keeping people physically active improves health status and survival rates among people with COPD. However, managing these two treatable traits can be extremely challenging for clinicians due to the complex intersectionality of factors influencing an individual's capacity, opportunity and motivation to engage in physical activity. This review presents the complex factors influencing exercise capacity ("can do"), levels of physical activity ("do do") and sedentary behaviours amongst people with COPD and provides practical recommendations on how clinicians can address some of these factors in practice. Most importantly, it highlights the importance of referring to pulmonary rehabilitation as a way to improve exercise capacity among people with COPD.

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)0.007
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0000.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.049
GPT teacher head0.338
Teacher spread0.289 · 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

Citations5
Published2024
Admission routes1
Has abstractyes

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