Reliability and validity of the instrument for scoring clinical outcomes of research for epidermolysis bullosa (iscorEB)
Bibliographic record
Abstract
Epidermolysis bullosa (EB) is a group of rare genetic blistering disorders that affects the skin and occasionally internal organs. Accurate estimates of disease severity of such complex disease in the context of research is difficult. We developed a tool called instrument for scoring clinical outcomes of research for Epidermolysis Bullosa (iscorEB) with the goal to assess the disease severity from both physician's and patient's perspective. In the current paper, we report the data from testing the iscorEB in 2 institutions from Canada and the USA. Thirty‐one patients and six physicians from various medical specialties took part in a study to demonstrate how consistent and good the score was at assessing the disease severity. We found that there was good agreement between physicians and between physicians and patients. We also demonstrated that iscorEB is able to differentiate between patients with mild, moderate and severe disease and between subtypes of EB.
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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 | 0.023 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".