International classification of functioning, disability, and health core sets for hearing loss: A discussion paper and invitation
Bibliographic record
Abstract
The World Health Organization’s International Classification of Functioning, Disability and Health (ICF) has adopted a multifactorial understanding of functioning and disability, merging a biomedical paradigm with a social paradigm into a wider understanding of human functioning. Altogether there are more than 1400 ICF-categories describing different aspects of human functioning and there is a need to developing short lists of ICF categories to facilitate use of the classification scheme in clinical practice. To our knowledge, there is currently no such standard measuring instrument to facilitate a common validated way of assessing the effects of hearing loss on the lives of adults. The aim of the project is the development of an internationally accepted, evidence-based, reliable, comprehensive and valid ICF Core Sets for Hearing Loss. The processes involved in this project are described in detail and the authors invite stakeholders, clinical experts and persons with hearing loss to actively participate in the development process.SumarioLa Clasificación sobre Funcionalidad, Discapacidad y Salud de la Organización Mundial de la Salud (ICF) ha adoptado un acercamiento multifactorial de la funcionalidad y la discapacidad, fusionando un paradigma biomédico con un paradigma social de una forma más amplia. En su conjunto hay más de 1400 categorías ICF que describen diferentes aspectos de la funcionalidad humana y existe la necesidad de desarrollar una lista corta de categorías ICF para facilitar el uso de la clasificación en un esquema para la práctica clínica. Es de nuestro conocimiento que actualmente no existe un instrumento de medición estándar que facilite una forma válida y cómoda para evaluar los efectos de la hipoacusia en la vida de los adultos. El propósito de este proyecto es desarrollar un conjunto básico de condiciones de salud ICF para la hipoacusia que sea internacionalmente aceptado, basado en evidencia, confiable e integral. Se describen en detalle los procesos implicados en este proyecto y los autores invitan a las personas interesadas, a los expertos clínicos y a las personas con hipoacusia a participar activamente en el desarrollo de este proceso.
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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 | 0.075 | 0.144 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.006 | 0.008 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.009 | 0.015 |
| Insufficient payload (model declined to judge) | 0.022 | 0.016 |
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".