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Record W2942782455 · doi:10.1097/ans.0000000000000247

Movement and Mobility

2019· article· en· W2942782455 on OpenAlexaff
E. J. Moulton, Rosemary Wilson, Kevin J. Deluzio

Bibliographic record

VenueAdvances in Nursing Science · 2019
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsQueen's University
Fundersnot available
KeywordsInternational Classification of Functioning, Disability and HealthMovement (music)Context (archaeology)Psychological interventionPsychologyApplied psychologyCognitive psychologyMedicineNursingRehabilitation

Abstract

fetched live from OpenAlex

This article provides an analysis of the concepts of movement and mobility within the context of the International Classification of Functioning, Disability, and Health (ICF) for patients' functioning, disability, and health. The methodology developed by Walker and Avant was used to clarify definitions, components, and relationships relevant to the 2 concepts and to the elements of the ICF framework. Definitions and the relationship between concepts are key information that clinicians and researchers need to measure the correct concept when they are assessing the effectiveness of interventions in nursing practice. Concept analysis findings are grounded by the notion that movement occurs when the body causes its own displacement and is explained by the basic principles of physics, human anatomy, and physiology. Mobility is then distinct because it is affected by the environment that the individual is in and can be assisted by any type of mobility aid. Mobility does not need to be generated by the individual's muscles but does need to be controlled by the individual who is mobile. An individual's mobility in his or her environment is important to his or her well-being and needs to be understood in relationship to his or her movements.

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 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 score0.300
Threshold uncertainty score0.174

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 head0.006
GPT teacher head0.321
Teacher spread0.314 · 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 teacher head, 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

Citations10
Published2019
Admission routes1
Has abstractyes

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