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Record W6963979151 · doi:10.25384/sage.c.6920032

International Classification of Function, Disability and Health (ICF) Word Mapping to Determine the Human Functioning Associated with Upper Extremity Surgery for Tetraplegia

2023· other· en· W6963979151 on OpenAlexaboutno aff

Bibliographic record

VenueSage Journals Data · 2023
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsTetraplegiaInternational Classification of Functioning, Disability and HealthRehabilitationGRASPQualitative analysisQualitative researchUpper limbActivities of daily living

Abstract

fetched live from OpenAlex

Understanding human functioning and disablement, the contributing factors and their interactions in individuals with tetraplegia is important since elective upper extremity (UE) reconstructive surgery is now offered earlier after injury prior to full recognition of what lies ahead. Qualitative and quantitative data were available from a prior series of mixed methods studies, including a case series design capturing the patients’ lived-experience perspectives of nerve or tendon transfer surgery, or not as the case may be. The objective of this study was to perform secondary data analysis to determine whether the recommended outcome tools being used by clinicians reflect the all important domains of functioning identified by people with tetraplegia who were considering UE reconstructive procedures. The original 18 candidate themes derived from qualitative analysis were reviewed in retrospect, along with a content analysis of the tools’ questions, undertaking word mapping links to the ICF taxonomy. The outcomes tools included in the content analysis were the Canadian Occupational Performance Measure, the Capabilities of Upper Extremity Questionnaire, The Personal Wellbeing Index, and the Grasp and Release Test. Comparison between clinical outcomes tools and the patient lived-experience data uniquely identified links to Chapter1 (b) Mental functions, which include consciousness, orientation, temperament/personality, energy/drive, and higher-level cognition.

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)0.007
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.671
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.221
GPT teacher head0.363
Teacher spread0.142 · 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.

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

Citations0
Published2023
Admission routes1
Has abstractyes

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