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Record W1964864755 · doi:10.1097/phm.0b013e31823d53cf

Illustrating Child-Specific Linking Issues Using the Child Health Questionnaire

2011· article· en· W1964864755 on OpenAlexaff
Nora Fayed, Alarcos Cieza, Jerome Bickenbach

Bibliographic record

VenueAmerican Journal of Physical Medicine & Rehabilitation · 2011
Typearticle
Languageen
FieldHealth Professions
TopicChild and Adolescent Health
Canadian institutionsMcMaster University
Fundersnot available
KeywordsInternational Classification of Functioning, Disability and HealthChild healthMedicineDevelopmental psychologyApplied psychologyPsychologyClinical psychologyFamily medicinePhysical therapy

Abstract

fetched live from OpenAlex

The publication of the International Classification of Disability, Functioning and Health Children and Youth (ICF-CY) version as a derived classification of the ICF has enabled child health and disability researchers to implement the classification into their work. There is little discussion available in the literature specifically about challenges associated with connecting ICF-CY to child health instruments. The objective of this study was to apply new reflections about linking and previous linking rules to a child-specific instrument using the Child Health Questionnaire as an example. We discovered the importance of knowledge in child health assessment as a linking requisite, issues with linking information about child behavior, the importance of clarifying the vantage point from which one is linking (e.g., child, parent, or family), and the fact that one should carefully consider the true purpose or targets of items before linking them to the ICF-CY, irrespective of the simple language used in the item. Finally, we propose the use of a new not-defined abbreviation to denote items that assess overall child development: not-defined-development (nd-dv).

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.883

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.048
GPT teacher head0.411
Teacher spread0.362 · 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 designOther design
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

Citations26
Published2011
Admission routes1
Has abstractyes

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