Classification of Functioning and Impairment: The Development of <scp>ICF C</scp>ore <scp>S</scp>ets for Autism Spectrum Disorder
Bibliographic record
Abstract
Given the variability seen in Autism Spectrum Disorder (ASD), accurate quantification of functioning is vital to studying outcome and quality of life in affected individuals. The International Classification of Functioning, Disability and Health (ICF) provides a comprehensive, universally accepted framework for the description of health-related functioning. ICF Core Sets are shortlists of ICF categories that are selected to capture those aspects of functioning that are most relevant when describing a person with a specific condition. In this paper, the authors preview the process for developing ICF Core Sets for ASD, a collaboration with the World Health Organization and the ICF Research Branch. The ICF Children and Youth version (ICF-CY) was derived from the ICF and designed to capture the specific situation of the developing child. As ASD affects individuals throughout the life span, and the ICF-CY includes all ICF categories, the ICF-CY will be used in this project ("ICF(-CY)" from now on). The ICF(-CY) categories to be included in the ICF Core Sets for ASD will be determined at an ICF Core Set Consensus Conference, where evidence from four preparatory studies (a systematic review, an expert survey, a patient and caregiver qualitative study, and a clinical cross-sectional study) will be integrated. Comprehensive and Brief ICF Core Sets for ASD will be developed with the goal of providing useful standards for research and clinical practice and generating a common language for functioning and impairment in ASD in different areas of life and across the life span.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.028 | 0.076 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.015 | 0.010 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".