The OMERACT-ICF Reference Group: Integrating the ICF into the OMERACT Process: Opportunities and Challenges
Bibliographic record
Abstract
At OMERACT 8 in May 2006 in Malta, the International Classification of Functioning, Disability and Health (ICF) was introduced as a universal model and a universal classification to describe human functioning. The potential usefulness of the ICF for the OMERACT process was highlighted and reported in a position paper following the OMERACT 8 meeting. Since then representatives of several OMERACT working groups with an interest in the ICF joined an OMERACT-ICF reference group. Most members had experience with the ICF and worked further to integrate the ICF into OMERACT. We describe the main roles of the ICF in the OMERACT process and the challenges when practice confronts theory.
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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 | 0.312 | 0.303 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.019 | 0.024 |
| Scholarly communication | 0.031 | 0.032 |
| Open science | 0.007 | 0.027 |
| Research integrity | 0.022 | 0.022 |
| Insufficient payload (model declined to judge) | 0.008 | 0.003 |
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".